Evaluating_RAG_with_DeepEval_English.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyNxLN03taH4RuRICa87u0oW",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "863c3add301b4ada90928022f4c6cae5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_530eb678faaa4ea6a9a6eef4b4a98911",
              "IPY_MODEL_b9559bb707004c4db510b939ae57d62f",
              "IPY_MODEL_a8e1544a350047e683d516d13b521e66"
            ],
            "layout": "IPY_MODEL_a569dda6d4cb414c9cbe44064431a4ba"
          }
        },
        "530eb678faaa4ea6a9a6eef4b4a98911": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d11db4459e174a0eadd7147bea1a8977",
            "placeholder": "​",
            "style": "IPY_MODEL_edc2731723a14b99ac3ab2030e0f96c2",
            "value": "config.json: 100%"
          }
        },
        "b9559bb707004c4db510b939ae57d62f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_7e6c0064a8134faaa7e499ac5a7f99f4",
            "max": 654,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_b7f7fa45f55e4b418cb7408ee2d27be2",
            "value": 654
          }
        },
        "a8e1544a350047e683d516d13b521e66": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_bd8eaffeab53482aa1b93fce57889003",
            "placeholder": "​",
            "style": "IPY_MODEL_3a928632bd194928bf8d36acf3d4b1cb",
            "value": " 654/654 [00:00&lt;00:00, 17.4kB/s]"
          }
        },
        "a569dda6d4cb414c9cbe44064431a4ba": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "d11db4459e174a0eadd7147bea1a8977": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "edc2731723a14b99ac3ab2030e0f96c2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "7e6c0064a8134faaa7e499ac5a7f99f4": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b7f7fa45f55e4b418cb7408ee2d27be2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "bd8eaffeab53482aa1b93fce57889003": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3a928632bd194928bf8d36acf3d4b1cb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "daf30a1654d64da2a19c1eda5753b278": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_8d9adbafb586432f86ac614956dfb7ef",
              "IPY_MODEL_8a3e75b8f6d64f91bb6a367a45b277a2",
              "IPY_MODEL_8ec8f3f7a22f4ec09ad76d57ff69245c"
            ],
            "layout": "IPY_MODEL_b7110c21626a4a4fa76d2384f0863eb5"
          }
        },
        "8d9adbafb586432f86ac614956dfb7ef": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_47569889f63346bb81fd2ca66bae4d3d",
            "placeholder": "​",
            "style": "IPY_MODEL_0ea7853f5afd40b387fd0fccafbd8273",
            "value": "model.safetensors.index.json: 100%"
          }
        },
        "8a3e75b8f6d64f91bb6a367a45b277a2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1c6faae82c0a415b8cf28d8366992256",
            "max": 23950,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_69e898cdd3e84782a647a366c97effc9",
            "value": 23950
          }
        },
        "8ec8f3f7a22f4ec09ad76d57ff69245c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e8de259c33244f73a66dbe69599536aa",
            "placeholder": "​",
            "style": "IPY_MODEL_dec6649a626e41fbb77ec05f7345ff81",
            "value": " 23.9k/23.9k [00:00&lt;00:00, 428kB/s]"
          }
        },
        "b7110c21626a4a4fa76d2384f0863eb5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "47569889f63346bb81fd2ca66bae4d3d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "0ea7853f5afd40b387fd0fccafbd8273": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "1c6faae82c0a415b8cf28d8366992256": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "69e898cdd3e84782a647a366c97effc9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "e8de259c33244f73a66dbe69599536aa": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "dec6649a626e41fbb77ec05f7345ff81": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "453f9047f92e4e89a22288a773e10c2b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_d3f40a68ac9942a29ad031c6a55e4965",
              "IPY_MODEL_ff8f2a5b567c4b52b4528e15c6ac43a4",
              "IPY_MODEL_406f6acfe23248b3a88fbde8e82e8c1c"
            ],
            "layout": "IPY_MODEL_888b5bba7b1748cb9b51d19e3be9b4e2"
          }
        },
        "d3f40a68ac9942a29ad031c6a55e4965": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_44b559b1101c447da0a3571257874e7e",
            "placeholder": "​",
            "style": "IPY_MODEL_1ce5ae05267a4d1da43b8eac190e4ed3",
            "value": "Downloading shards: 100%"
          }
        },
        "ff8f2a5b567c4b52b4528e15c6ac43a4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_120cc191083d433184b2cd1e9404f9e2",
            "max": 4,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_1921e32cc136413f952782584b6df067",
            "value": 4
          }
        },
        "406f6acfe23248b3a88fbde8e82e8c1c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_6d1f697640de4828bc11e47ec3a19304",
            "placeholder": "​",
            "style": "IPY_MODEL_553cc595495c43d6b3154e09022ca6a5",
            "value": " 4/4 [02:18&lt;00:00, 29.50s/it]"
          }
        },
        "888b5bba7b1748cb9b51d19e3be9b4e2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "44b559b1101c447da0a3571257874e7e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1ce5ae05267a4d1da43b8eac190e4ed3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "120cc191083d433184b2cd1e9404f9e2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1921e32cc136413f952782584b6df067": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "6d1f697640de4828bc11e47ec3a19304": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "553cc595495c43d6b3154e09022ca6a5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a7ef3fa6dfaa4cc48fd1111747fcddca": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_a1f5e485112645fd88886f65a3aebc83",
              "IPY_MODEL_bb5a3ab3e81f4f37881d0fa20aaaaab5",
              "IPY_MODEL_2169262c002d4f1e958ce18b5c8ce307"
            ],
            "layout": "IPY_MODEL_1d6399ded25d4aba9d49ba755fdb4f42"
          }
        },
        "a1f5e485112645fd88886f65a3aebc83": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_60563bbbd3ad4663a8a5f4cd81914d58",
            "placeholder": "​",
            "style": "IPY_MODEL_305b71e96e9349b8bbd6ab66fb4a74d9",
            "value": "model-00001-of-00004.safetensors: 100%"
          }
        },
        "bb5a3ab3e81f4f37881d0fa20aaaaab5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4f16820c111d47b1b5bee0b99fc113c3",
            "max": 4976698672,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_a62005aba26a475fb99e20b4c9f74e34",
            "value": 4976698672
          }
        },
        "2169262c002d4f1e958ce18b5c8ce307": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4379125630da477b853b157bcbc49f45",
            "placeholder": "​",
            "style": "IPY_MODEL_7c7ae27f41614f5d99d85641d76080ea",
            "value": " 4.98G/4.98G [00:42&lt;00:00, 39.2MB/s]"
          }
        },
        "1d6399ded25d4aba9d49ba755fdb4f42": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "60563bbbd3ad4663a8a5f4cd81914d58": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "305b71e96e9349b8bbd6ab66fb4a74d9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "4f16820c111d47b1b5bee0b99fc113c3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a62005aba26a475fb99e20b4c9f74e34": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "4379125630da477b853b157bcbc49f45": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7c7ae27f41614f5d99d85641d76080ea": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "58dd5057309049afa2d0ec0cd59875ef": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_e9933a55e8aa4cbf9fd8687fcd4894b5",
              "IPY_MODEL_83f5b793ae8f4bd6ada850587c0ca6c1",
              "IPY_MODEL_197bcc20d5da4719aa9d53dc7b3c7ed3"
            ],
            "layout": "IPY_MODEL_705ffa8a11c74c059dedeab680fe6e44"
          }
        },
        "e9933a55e8aa4cbf9fd8687fcd4894b5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1733a2a571ab4df5ad9033b7a13dc44a",
            "placeholder": "​",
            "style": "IPY_MODEL_1f78ef7b7ab54afb861ee5a87e318f72",
            "value": "model-00002-of-00004.safetensors: 100%"
          }
        },
        "83f5b793ae8f4bd6ada850587c0ca6c1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d0d10a3810f14a42b3086fb7e3b8ea3a",
            "max": 4999802720,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_3a4599060f2844049b527f617c4e4d68",
            "value": 4999802720
          }
        },
        "197bcc20d5da4719aa9d53dc7b3c7ed3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d475ad469cdb4e12892ccf57cb4b8153",
            "placeholder": "​",
            "style": "IPY_MODEL_8ceb375e5347461da166a7de191de83b",
            "value": " 5.00G/5.00G [00:42&lt;00:00, 13.8MB/s]"
          }
        },
        "705ffa8a11c74c059dedeab680fe6e44": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1733a2a571ab4df5ad9033b7a13dc44a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1f78ef7b7ab54afb861ee5a87e318f72": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d0d10a3810f14a42b3086fb7e3b8ea3a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3a4599060f2844049b527f617c4e4d68": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "d475ad469cdb4e12892ccf57cb4b8153": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8ceb375e5347461da166a7de191de83b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "1294a2ce9d0347ca8bcf1018f618dbf4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_8d54bcfe48e04fc39c918ba3dfce124a",
              "IPY_MODEL_11a5718c43c14ff88825ae75b6f55ffe",
              "IPY_MODEL_7f2a597b351341b5b9f8c3e2df2f96f5"
            ],
            "layout": "IPY_MODEL_90599c8b858d460f9a70e067fdbce04c"
          }
        },
        "8d54bcfe48e04fc39c918ba3dfce124a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c42076a667984e40a7b0e42f93acefd7",
            "placeholder": "​",
            "style": "IPY_MODEL_60fd17ff6af341a2a20735410ba40473",
            "value": "model-00003-of-00004.safetensors: 100%"
          }
        },
        "11a5718c43c14ff88825ae75b6f55ffe": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_7e87a4b9e69c410889331df006f9b8cb",
            "max": 4915916176,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_b983e66a3d844ce8a0459c126f31dfa7",
            "value": 4915916176
          }
        },
        "7f2a597b351341b5b9f8c3e2df2f96f5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ade41be3366f4284afc241c25bfcd076",
            "placeholder": "​",
            "style": "IPY_MODEL_f0ffee98024d45f3892d7f4b8317da78",
            "value": " 4.92G/4.92G [00:47&lt;00:00, 19.2MB/s]"
          }
        },
        "90599c8b858d460f9a70e067fdbce04c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c42076a667984e40a7b0e42f93acefd7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "60fd17ff6af341a2a20735410ba40473": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "7e87a4b9e69c410889331df006f9b8cb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b983e66a3d844ce8a0459c126f31dfa7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "ade41be3366f4284afc241c25bfcd076": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f0ffee98024d45f3892d7f4b8317da78": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "5e7092382d364ef3895a8ac9fb9894e1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_64822ea361544864ba6aa34fd6b62087",
              "IPY_MODEL_7d38e788a5064478baa273ed97c8890f",
              "IPY_MODEL_a488625bbd6d4e489f2bb45ff7401849"
            ],
            "layout": "IPY_MODEL_b76be3b31a8d44f99b144d849c6c2ce5"
          }
        },
        "64822ea361544864ba6aa34fd6b62087": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_80c4181b627844a98ad9313dc1aa7f9b",
            "placeholder": "​",
            "style": "IPY_MODEL_cb5c8c788c85498b959a0ec34889bf75",
            "value": "model-00004-of-00004.safetensors: 100%"
          }
        },
        "7d38e788a5064478baa273ed97c8890f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_51dee1f66e534de38bf0d90b55096c32",
            "max": 1168138808,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_e6599930c9e846328e17f30cb355a632",
            "value": 1168138808
          }
        },
        "a488625bbd6d4e489f2bb45ff7401849": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_840c1377996641929d3c7d371dfe0722",
            "placeholder": "​",
            "style": "IPY_MODEL_b011b27b93b74f8baf2081cda8aec1a2",
            "value": " 1.17G/1.17G [00:06&lt;00:00, 219MB/s]"
          }
        },
        "b76be3b31a8d44f99b144d849c6c2ce5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "80c4181b627844a98ad9313dc1aa7f9b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "cb5c8c788c85498b959a0ec34889bf75": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "51dee1f66e534de38bf0d90b55096c32": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e6599930c9e846328e17f30cb355a632": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "840c1377996641929d3c7d371dfe0722": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b011b27b93b74f8baf2081cda8aec1a2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "6df3513c6ac442498581d4dbe1ae6b3e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_0fe88da730cb4e04bb2410f3de253f13",
              "IPY_MODEL_147093077d8c4d129eef9b5cc37d7075",
              "IPY_MODEL_27c131b97baf471d9b618f311093659a"
            ],
            "layout": "IPY_MODEL_2e0383645da54b2b951bad46fa3298cd"
          }
        },
        "0fe88da730cb4e04bb2410f3de253f13": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a495a6b791934fd0b2f9e39b75bc2f15",
            "placeholder": "​",
            "style": "IPY_MODEL_a0c81817840743d2ab0c0b2c83501410",
            "value": "Loading checkpoint shards: 100%"
          }
        },
        "147093077d8c4d129eef9b5cc37d7075": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_7bb9efbbe62e42b89be8d43687032849",
            "max": 4,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_f2bfd3702a604a90bebb4d8745ce0acb",
            "value": 4
          }
        },
        "27c131b97baf471d9b618f311093659a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_dace7073dc9940afba2a663028b2891f",
            "placeholder": "​",
            "style": "IPY_MODEL_1fe124290fe64b9a957f3c170a7f152e",
            "value": " 4/4 [01:14&lt;00:00, 16.21s/it]"
          }
        },
        "2e0383645da54b2b951bad46fa3298cd": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a495a6b791934fd0b2f9e39b75bc2f15": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a0c81817840743d2ab0c0b2c83501410": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "7bb9efbbe62e42b89be8d43687032849": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f2bfd3702a604a90bebb4d8745ce0acb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "dace7073dc9940afba2a663028b2891f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1fe124290fe64b9a957f3c170a7f152e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "2508aeb666d145238dac32d30cadd525": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_f4d191fc7e194e56a297b5016973d7db",
              "IPY_MODEL_e91e7cf9ad4f4cd8a9814ac62b7032be",
              "IPY_MODEL_77ddf7e816074d6bb76a6a90db6ee760"
            ],
            "layout": "IPY_MODEL_90809c526f9f416ab493df5144e42e35"
          }
        },
        "f4d191fc7e194e56a297b5016973d7db": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_37ba40df783f40978c6df03d64b19b61",
            "placeholder": "​",
            "style": "IPY_MODEL_08d9675d68204630af3682d76eafcdce",
            "value": "generation_config.json: 100%"
          }
        },
        "e91e7cf9ad4f4cd8a9814ac62b7032be": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d9736cd5230f4823a01c205ad62225e9",
            "max": 187,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_7a631172f02842328ca28c843e750ea7",
            "value": 187
          }
        },
        "77ddf7e816074d6bb76a6a90db6ee760": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_19ec6824f3d4497b8640cd50efd316e5",
            "placeholder": "​",
            "style": "IPY_MODEL_86caea32898b4c078c71b27b0b4245f8",
            "value": " 187/187 [00:00&lt;00:00, 10.4kB/s]"
          }
        },
        "90809c526f9f416ab493df5144e42e35": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "37ba40df783f40978c6df03d64b19b61": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "08d9675d68204630af3682d76eafcdce": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d9736cd5230f4823a01c205ad62225e9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7a631172f02842328ca28c843e750ea7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "19ec6824f3d4497b8640cd50efd316e5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "86caea32898b4c078c71b27b0b4245f8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "54585de6cad74c82a1fade98238e9360": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_bbccc4dbf4f34080bd8e417315fd32d4",
              "IPY_MODEL_86a5ee4774b14be78890c2616e26f0ea",
              "IPY_MODEL_4b6c66b62f2b4b4493836cf4da3907c9"
            ],
            "layout": "IPY_MODEL_80e2d5e60c774185afd73ece74c1008e"
          }
        },
        "bbccc4dbf4f34080bd8e417315fd32d4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_965d2589664f4134b89e04b8e5cbc5d6",
            "placeholder": "​",
            "style": "IPY_MODEL_96d2d6a9c59d4f618cae0ba9043189ed",
            "value": "tokenizer_config.json: 100%"
          }
        },
        "86a5ee4774b14be78890c2616e26f0ea": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_0dc2e08a2e97467d9db6a99d476ce954",
            "max": 50977,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_74f76d0a45e644429744b7f3b62e1e07",
            "value": 50977
          }
        },
        "4b6c66b62f2b4b4493836cf4da3907c9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_efb5e89370bb47f09b69a416099b0958",
            "placeholder": "​",
            "style": "IPY_MODEL_f4d0f8bfcb844d82aa953d0b8604c845",
            "value": " 51.0k/51.0k [00:00&lt;00:00, 2.39MB/s]"
          }
        },
        "80e2d5e60c774185afd73ece74c1008e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "965d2589664f4134b89e04b8e5cbc5d6": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "96d2d6a9c59d4f618cae0ba9043189ed": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "0dc2e08a2e97467d9db6a99d476ce954": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "74f76d0a45e644429744b7f3b62e1e07": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "efb5e89370bb47f09b69a416099b0958": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f4d0f8bfcb844d82aa953d0b8604c845": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "3e823502f01e4ea29aee24055d5587ff": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_fe472288c460426293e444c66f92b0cd",
              "IPY_MODEL_7791cf340140459b9926f7575c829f60",
              "IPY_MODEL_cc1258c8a7c54067b1da7784b7fb2ee1"
            ],
            "layout": "IPY_MODEL_238f4d1ed4ed45bcb9293ab2ac9ffc5a"
          }
        },
        "fe472288c460426293e444c66f92b0cd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c51301debbf7442492351b284f55ff5c",
            "placeholder": "​",
            "style": "IPY_MODEL_f391142a598d41919d5554e927b081b6",
            "value": "tokenizer.json: 100%"
          }
        },
        "7791cf340140459b9926f7575c829f60": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1c80a2546d5c45708a440c7a7c7c721b",
            "max": 9085698,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_d41d26246a654b8193792b03ab53f80b",
            "value": 9085698
          }
        },
        "cc1258c8a7c54067b1da7784b7fb2ee1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e761419fa598426fa912a7e1d47164ff",
            "placeholder": "​",
            "style": "IPY_MODEL_e86355e43f1647b499d732fcddca558f",
            "value": " 9.09M/9.09M [00:00&lt;00:00, 22.3MB/s]"
          }
        },
        "238f4d1ed4ed45bcb9293ab2ac9ffc5a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c51301debbf7442492351b284f55ff5c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f391142a598d41919d5554e927b081b6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "1c80a2546d5c45708a440c7a7c7c721b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "d41d26246a654b8193792b03ab53f80b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "e761419fa598426fa912a7e1d47164ff": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e86355e43f1647b499d732fcddca558f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d00c7b8a854941aba5a1b9d596666495": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_64a5888bd3984de397dd7cd43bd6ea36",
              "IPY_MODEL_45e6a8cb4b7b4de3bab1ae5cddd55a7c",
              "IPY_MODEL_86ff38326b814b1691c40f9f11020bcb"
            ],
            "layout": "IPY_MODEL_8044e6afb26849faa5d32610fc1085c0"
          }
        },
        "64a5888bd3984de397dd7cd43bd6ea36": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_91e864f9451c4e56ac84cfa88d56edef",
            "placeholder": "​",
            "style": "IPY_MODEL_120286dbd4124e40843e47f6d83b6b40",
            "value": "special_tokens_map.json: 100%"
          }
        },
        "45e6a8cb4b7b4de3bab1ae5cddd55a7c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_fa77c3b9a89f4bd7827b2ecf838b2d47",
            "max": 73,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_4377155eee1e41b4b06dd55e06ab7e66",
            "value": 73
          }
        },
        "86ff38326b814b1691c40f9f11020bcb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e537bad67f3c4eb7b301bd0d188b6f5c",
            "placeholder": "​",
            "style": "IPY_MODEL_a958807551564697b6d319dfd99a7f9d",
            "value": " 73.0/73.0 [00:00&lt;00:00, 4.90kB/s]"
          }
        },
        "8044e6afb26849faa5d32610fc1085c0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "91e864f9451c4e56ac84cfa88d56edef": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "120286dbd4124e40843e47f6d83b6b40": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "fa77c3b9a89f4bd7827b2ecf838b2d47": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "4377155eee1e41b4b06dd55e06ab7e66": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "e537bad67f3c4eb7b301bd0d188b6f5c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a958807551564697b6d319dfd99a7f9d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "6b521c28ea22456caa13de3727035208": {
          "model_module": "@jupyter-widgets/output",
          "model_name": "OutputModel",
          "model_module_version": "1.0.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_model_name": "OutputModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/output",
            "_view_module_version": "1.0.0",
            "_view_name": "OutputView",
            "layout": "IPY_MODEL_0608260bfa734f419f13d116a7a25bca",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "\u001b[38;2;106;0;255m⠇\u001b[0m ✨ You're running DeepEval's latest \u001b[38;2;106;0;255mAnswer Relevancy Metric\u001b[0m! \u001b[38;2;55;65;81m(using Llama-3 8B, strict=False, async_mode=True)...\u001b[0m\n",
                  "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">⠇</span> ✨ You're running DeepEval's latest <span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">Answer Relevancy Metric</span>! <span style=\"color: #374151; text-decoration-color: #374151\">(using Llama-3 8B, strict=False, async_mode=True)...</span>\n</pre>\n"
                },
                "metadata": {}
              }
            ]
          }
        },
        "0608260bfa734f419f13d116a7a25bca": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "07d59bedd92046dda65ee56483499bb2": {
          "model_module": "@jupyter-widgets/output",
          "model_name": "OutputModel",
          "model_module_version": "1.0.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_model_name": "OutputModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/output",
            "_view_module_version": "1.0.0",
            "_view_name": "OutputView",
            "layout": "IPY_MODEL_7c61af1d2b18466985437b054c9bdcf7",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "\u001b[38;2;106;0;255m⠹\u001b[0m ✨ You're running DeepEval's latest \u001b[38;2;106;0;255mBias Metric\u001b[0m! \u001b[38;2;55;65;81m(using Llama-3 8B, strict=False, async_mode=True)...\u001b[0m\n",
                  "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">⠹</span> ✨ You're running DeepEval's latest <span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">Bias Metric</span>! <span style=\"color: #374151; text-decoration-color: #374151\">(using Llama-3 8B, strict=False, async_mode=True)...</span>\n</pre>\n"
                },
                "metadata": {}
              }
            ]
          }
        },
        "7c61af1d2b18466985437b054c9bdcf7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "98abd9bd997e46bf8724962fb4c6e7a6": {
          "model_module": "@jupyter-widgets/output",
          "model_name": "OutputModel",
          "model_module_version": "1.0.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_model_name": "OutputModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/output",
            "_view_module_version": "1.0.0",
            "_view_name": "OutputView",
            "layout": "IPY_MODEL_136828056f85419d8fbeb8152e32f398",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "\u001b[38;2;106;0;255m⠹\u001b[0m ✨ You're running DeepEval's latest \u001b[38;2;106;0;255mBias Metric\u001b[0m! \u001b[38;2;55;65;81m(using Llama-3 8B, strict=False, async_mode=True)...\u001b[0m\n",
                  "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">⠹</span> ✨ You're running DeepEval's latest <span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">Bias Metric</span>! <span style=\"color: #374151; text-decoration-color: #374151\">(using Llama-3 8B, strict=False, async_mode=True)...</span>\n</pre>\n"
                },
                "metadata": {}
              }
            ]
          }
        },
        "136828056f85419d8fbeb8152e32f398": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ba25c94724b94c99b7a4e22a61946615": {
          "model_module": "@jupyter-widgets/output",
          "model_name": "OutputModel",
          "model_module_version": "1.0.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_model_name": "OutputModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/output",
            "_view_module_version": "1.0.0",
            "_view_name": "OutputView",
            "layout": "IPY_MODEL_3101992b156e44879058d885eadfdbfa",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "\u001b[38;2;106;0;255m⠋\u001b[0m ✨ You're running DeepEval's latest \u001b[38;2;106;0;255mFaithfulness Metric\u001b[0m! \u001b[38;2;55;65;81m(using Llama-3 8B, strict=False, async_mode=True)...\u001b[0m\n",
                  "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">⠋</span> ✨ You're running DeepEval's latest <span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">Faithfulness Metric</span>! <span style=\"color: #374151; text-decoration-color: #374151\">(using Llama-3 8B, strict=False, async_mode=True)...</span>\n</pre>\n"
                },
                "metadata": {}
              }
            ]
          }
        },
        "3101992b156e44879058d885eadfdbfa": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3d25f695108b481a9f90af61e9603653": {
          "model_module": "@jupyter-widgets/output",
          "model_name": "OutputModel",
          "model_module_version": "1.0.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_model_name": "OutputModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/output",
            "_view_module_version": "1.0.0",
            "_view_name": "OutputView",
            "layout": "IPY_MODEL_91cc6c89db044522943f566bbb24e42b",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "\u001b[38;2;106;0;255m⠹\u001b[0m ✨ You're running DeepEval's latest \u001b[38;2;106;0;255mFaithfulness Metric\u001b[0m! \u001b[38;2;55;65;81m(using Llama-3 8B, strict=False, async_mode=True)...\u001b[0m\n",
                  "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">⠹</span> ✨ You're running DeepEval's latest <span style=\"color: #6a00ff; text-decoration-color: #6a00ff\">Faithfulness Metric</span>! <span style=\"color: #374151; text-decoration-color: #374151\">(using Llama-3 8B, strict=False, async_mode=True)...</span>\n</pre>\n"
                },
                "metadata": {}
              }
            ]
          }
        },
        "91cc6c89db044522943f566bbb24e42b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hoangcuongnguyen2001/RAG_lessons/blob/main/Evaluating_RAG_with_DeepEval_English.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Evaluating RAG pipelines and LLM systems with DeepEval**\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "s0UNbxvVbh7L"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Many libraries and platforms have been developed to evaluate the effectiveness or accuracy of RAG pipelines, such as DeepEval, RAGAS and TRULens. I will talk about DeepEval, a model developed by a startup (Confident AI): [https://docs.confident-ai.com/](https://www.google.com/url?q=https%3A%2F%2Fdocs.confident-ai.com%2F).\n",
        "\n",
        "You might ask, why we use DeepEval in this presentation? Well, there are several reasons:\n",
        "\n",
        "1. DeepEval is an open-source model, so everyone could use without need of permission from any author, and without paying (compared to other proprietary platforms, such as Amazon Bedrock).\n",
        "2. There are various metrics that DeepEval supports, such as bias, toxicity or answer relevancy.\n",
        "3. In many platforms, you have to upload an annotated dataset (with questions and correct answers to check answers). In DeepEval, you only need a question and the answer provided by RAG systems (and sometimes, the correct answer)."
      ],
      "metadata": {
        "id": "c4O7ZFF0zWLh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "For how DeepEval works, there is a paper about this: [G-EVAL: NLGEvaluation using GPT-4 with Better Human Alignment](https://arxiv.org/pdf/2303.16634).\n",
        "\n",
        "![image.png](data:image/png;base64,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)\n",
        "\n",
        "\n",
        "Basically, you will set up a LLM (proprietary ones like GPT-4, Gemini with Google Vertex API, etc., or open-source ones, such as Llama 3, Mistral-7b, etc.). DeepEval will take your answers, and ask LLM that you set up to see how they align with any metric you set up. Sometimes LLM will need to compare it with the correct answer (or ground truth).\n",
        "\n",
        "What are advantages of this approach? From Confident AI itself:\n",
        "\n",
        "\n",
        "\n",
        "> Almost all default metrics offered by `deepeval` are LLM-Evals, which means they are evaluated using LLMs. This is deliberate because LLM-Evals are versatile in nature and better align with human expectations when compared to traditional model based approaches.\n",
        "\n",
        "> `deepeval`'s LLM-Evals are a step up to other implementations because they:\n",
        "\n",
        "\n",
        "\n",
        "> - are extra reliable as LLMs are only used for extremely specific tasks during evaluation to greatly reduce stochasticity and flakiness in scores.\n",
        "- provide a comprehensive reason for the scores computed.\n",
        "- can be computed using any LLM.\n",
        "\n",
        "\n",
        "\n",
        "In this example, we will use Llama3-7b as the LLM for DeepEval to work."
      ],
      "metadata": {
        "id": "XRBD33TH07gr"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Setting up prerequisite libraries:***"
      ],
      "metadata": {
        "id": "ojVZt82y2Vxj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "We will first need to install prerequisite libraries, to deploy DeepEval. Please note that it needs an LLM to work, so we will need some necessary libraries for LLM to work, such as `transformers`,` torch`, `bitsandbytes`, `accelerate`."
      ],
      "metadata": {
        "id": "e8cFo3OF2u0F"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install deepeval"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8gIDrIGDVbrG",
        "outputId": "4e624e9a-b2fa-4bcb-f886-d68b7140421d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting deepeval\n",
            "  Downloading deepeval-0.21.74-py3-none-any.whl.metadata (996 bytes)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from deepeval) (2.31.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from deepeval) (4.66.4)\n",
            "Requirement already satisfied: pytest in /usr/local/lib/python3.10/dist-packages (from deepeval) (7.4.4)\n",
            "Requirement already satisfied: tabulate in /usr/local/lib/python3.10/dist-packages (from deepeval) (0.9.0)\n",
            "Requirement already satisfied: typer in /usr/local/lib/python3.10/dist-packages (from deepeval) (0.12.3)\n",
            "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from deepeval) (13.7.1)\n",
            "Collecting protobuf==4.25.1 (from deepeval)\n",
            "  Downloading protobuf-4.25.1-cp37-abi3-manylinux2014_x86_64.whl.metadata (541 bytes)\n",
            "Requirement already satisfied: pydantic in /usr/local/lib/python3.10/dist-packages (from deepeval) (2.8.2)\n",
            "Collecting sentry-sdk (from deepeval)\n",
            "  Downloading sentry_sdk-2.12.0-py2.py3-none-any.whl.metadata (9.8 kB)\n",
            "Collecting pytest-repeat (from deepeval)\n",
            "  Downloading pytest_repeat-0.9.3-py3-none-any.whl.metadata (4.9 kB)\n",
            "Collecting pytest-xdist (from deepeval)\n",
            "  Downloading pytest_xdist-3.6.1-py3-none-any.whl.metadata (4.3 kB)\n",
            "Collecting portalocker (from deepeval)\n",
            "  Downloading portalocker-2.10.1-py3-none-any.whl.metadata (8.5 kB)\n",
            "Collecting langchain (from deepeval)\n",
            "  Downloading langchain-0.2.11-py3-none-any.whl.metadata (7.1 kB)\n",
            "Collecting langchain-core (from deepeval)\n",
            "  Downloading langchain_core-0.2.25-py3-none-any.whl.metadata (6.2 kB)\n",
            "Collecting langchain-openai (from deepeval)\n",
            "  Downloading langchain_openai-0.1.19-py3-none-any.whl.metadata (2.6 kB)\n",
            "Collecting ragas (from deepeval)\n",
            "  Downloading ragas-0.1.12-py3-none-any.whl.metadata (5.2 kB)\n",
            "Collecting docx2txt~=0.8 (from deepeval)\n",
            "  Downloading docx2txt-0.8.tar.gz (2.8 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: importlib-metadata>=6.0.2 in /usr/local/lib/python3.10/dist-packages (from deepeval) (8.2.0)\n",
            "Collecting tenacity~=8.4.1 (from deepeval)\n",
            "  Downloading tenacity-8.4.2-py3-none-any.whl.metadata (1.2 kB)\n",
            "Collecting opentelemetry-api==1.24.0 (from deepeval)\n",
            "  Downloading opentelemetry_api-1.24.0-py3-none-any.whl.metadata (1.3 kB)\n",
            "Collecting opentelemetry-sdk==1.24.0 (from deepeval)\n",
            "  Downloading opentelemetry_sdk-1.24.0-py3-none-any.whl.metadata (1.4 kB)\n",
            "Collecting opentelemetry-exporter-otlp-proto-grpc==1.24.0 (from deepeval)\n",
            "  Downloading opentelemetry_exporter_otlp_proto_grpc-1.24.0-py3-none-any.whl.metadata (2.2 kB)\n",
            "Collecting grpcio==1.63.0 (from deepeval)\n",
            "  Downloading grpcio-1.63.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.2 kB)\n",
            "Collecting deprecated>=1.2.6 (from opentelemetry-api==1.24.0->deepeval)\n",
            "  Downloading Deprecated-1.2.14-py2.py3-none-any.whl.metadata (5.4 kB)\n",
            "Collecting importlib-metadata>=6.0.2 (from deepeval)\n",
            "  Downloading importlib_metadata-7.0.0-py3-none-any.whl.metadata (4.9 kB)\n",
            "Requirement already satisfied: googleapis-common-protos~=1.52 in /usr/local/lib/python3.10/dist-packages (from opentelemetry-exporter-otlp-proto-grpc==1.24.0->deepeval) (1.63.2)\n",
            "Collecting opentelemetry-exporter-otlp-proto-common==1.24.0 (from opentelemetry-exporter-otlp-proto-grpc==1.24.0->deepeval)\n",
            "  Downloading opentelemetry_exporter_otlp_proto_common-1.24.0-py3-none-any.whl.metadata (1.7 kB)\n",
            "Collecting opentelemetry-proto==1.24.0 (from opentelemetry-exporter-otlp-proto-grpc==1.24.0->deepeval)\n",
            "  Downloading opentelemetry_proto-1.24.0-py3-none-any.whl.metadata (2.2 kB)\n",
            "Collecting opentelemetry-semantic-conventions==0.45b0 (from opentelemetry-sdk==1.24.0->deepeval)\n",
            "  Downloading opentelemetry_semantic_conventions-0.45b0-py3-none-any.whl.metadata (2.2 kB)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4 in /usr/local/lib/python3.10/dist-packages (from opentelemetry-sdk==1.24.0->deepeval) (4.12.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=6.0.2->deepeval) (3.19.2)\n",
            "Requirement already satisfied: PyYAML>=5.3 in /usr/local/lib/python3.10/dist-packages (from langchain->deepeval) (6.0.1)\n",
            "Requirement already satisfied: SQLAlchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from langchain->deepeval) (2.0.31)\n",
            "Requirement already satisfied: aiohttp<4.0.0,>=3.8.3 in /usr/local/lib/python3.10/dist-packages (from langchain->deepeval) (3.9.5)\n",
            "Requirement already satisfied: async-timeout<5.0.0,>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from langchain->deepeval) (4.0.3)\n",
            "Collecting langchain-text-splitters<0.3.0,>=0.2.0 (from langchain->deepeval)\n",
            "  Downloading langchain_text_splitters-0.2.2-py3-none-any.whl.metadata (2.1 kB)\n",
            "Collecting langsmith<0.2.0,>=0.1.17 (from langchain->deepeval)\n",
            "  Downloading langsmith-0.1.94-py3-none-any.whl.metadata (13 kB)\n",
            "Requirement already satisfied: numpy<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain->deepeval) (1.26.4)\n",
            "Collecting jsonpatch<2.0,>=1.33 (from langchain-core->deepeval)\n",
            "  Downloading jsonpatch-1.33-py2.py3-none-any.whl.metadata (3.0 kB)\n",
            "Requirement already satisfied: packaging<25,>=23.2 in /usr/local/lib/python3.10/dist-packages (from langchain-core->deepeval) (24.1)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic->deepeval) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.20.1 in /usr/local/lib/python3.10/dist-packages (from pydantic->deepeval) (2.20.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->deepeval) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->deepeval) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->deepeval) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->deepeval) (2024.7.4)\n",
            "Collecting openai<2.0.0,>=1.32.0 (from langchain-openai->deepeval)\n",
            "  Downloading openai-1.37.1-py3-none-any.whl.metadata (22 kB)\n",
            "Collecting tiktoken<1,>=0.7 (from langchain-openai->deepeval)\n",
            "  Downloading tiktoken-0.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.6 kB)\n",
            "Requirement already satisfied: iniconfig in /usr/local/lib/python3.10/dist-packages (from pytest->deepeval) (2.0.0)\n",
            "Requirement already satisfied: pluggy<2.0,>=0.12 in /usr/local/lib/python3.10/dist-packages (from pytest->deepeval) (1.5.0)\n",
            "Requirement already satisfied: exceptiongroup>=1.0.0rc8 in /usr/local/lib/python3.10/dist-packages (from pytest->deepeval) (1.2.2)\n",
            "Requirement already satisfied: tomli>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from pytest->deepeval) (2.0.1)\n",
            "Collecting execnet>=2.1 (from pytest-xdist->deepeval)\n",
            "  Downloading execnet-2.1.1-py3-none-any.whl.metadata (2.9 kB)\n",
            "Collecting datasets (from ragas->deepeval)\n",
            "  Downloading datasets-2.20.0-py3-none-any.whl.metadata (19 kB)\n",
            "Collecting langchain-community (from ragas->deepeval)\n",
            "  Downloading langchain_community-0.2.10-py3-none-any.whl.metadata (2.7 kB)\n",
            "Collecting pysbd>=0.3.4 (from ragas->deepeval)\n",
            "  Downloading pysbd-0.3.4-py3-none-any.whl.metadata (6.1 kB)\n",
            "Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.10/dist-packages (from ragas->deepeval) (1.6.0)\n",
            "Collecting appdirs (from ragas->deepeval)\n",
            "  Downloading appdirs-1.4.4-py2.py3-none-any.whl.metadata (9.0 kB)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->deepeval) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->deepeval) (2.16.1)\n",
            "Requirement already satisfied: click>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from typer->deepeval) (8.1.7)\n",
            "Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.10/dist-packages (from typer->deepeval) (1.5.4)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain->deepeval) (1.3.1)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain->deepeval) (23.2.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain->deepeval) (1.4.1)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain->deepeval) (6.0.5)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain->deepeval) (1.9.4)\n",
            "Requirement already satisfied: wrapt<2,>=1.10 in /usr/local/lib/python3.10/dist-packages (from deprecated>=1.2.6->opentelemetry-api==1.24.0->deepeval) (1.14.1)\n",
            "Collecting jsonpointer>=1.9 (from jsonpatch<2.0,>=1.33->langchain-core->deepeval)\n",
            "  Downloading jsonpointer-3.0.0-py2.py3-none-any.whl.metadata (2.3 kB)\n",
            "Collecting orjson<4.0.0,>=3.9.14 (from langsmith<0.2.0,>=0.1.17->langchain->deepeval)\n",
            "  Downloading orjson-3.10.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (50 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.4/50.4 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->deepeval) (0.1.2)\n",
            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai<2.0.0,>=1.32.0->langchain-openai->deepeval) (3.7.1)\n",
            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from openai<2.0.0,>=1.32.0->langchain-openai->deepeval) (1.7.0)\n",
            "Collecting httpx<1,>=0.23.0 (from openai<2.0.0,>=1.32.0->langchain-openai->deepeval)\n",
            "  Downloading httpx-0.27.0-py3-none-any.whl.metadata (7.2 kB)\n",
            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from openai<2.0.0,>=1.32.0->langchain-openai->deepeval) (1.3.1)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain->deepeval) (3.0.3)\n",
            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken<1,>=0.7->langchain-openai->deepeval) (2024.5.15)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets->ragas->deepeval) (3.15.4)\n",
            "Collecting pyarrow>=15.0.0 (from datasets->ragas->deepeval)\n",
            "  Downloading pyarrow-17.0.0-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (3.3 kB)\n",
            "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets->ragas->deepeval) (0.6)\n",
            "Collecting dill<0.3.9,>=0.3.0 (from datasets->ragas->deepeval)\n",
            "  Downloading dill-0.3.8-py3-none-any.whl.metadata (10 kB)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets->ragas->deepeval) (2.1.4)\n",
            "Collecting requests (from deepeval)\n",
            "  Downloading requests-2.32.3-py3-none-any.whl.metadata (4.6 kB)\n",
            "Collecting xxhash (from datasets->ragas->deepeval)\n",
            "  Downloading xxhash-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (12 kB)\n",
            "Collecting multiprocess (from datasets->ragas->deepeval)\n",
            "  Downloading multiprocess-0.70.16-py310-none-any.whl.metadata (7.2 kB)\n",
            "Collecting fsspec<=2024.5.0,>=2023.1.0 (from fsspec[http]<=2024.5.0,>=2023.1.0->datasets->ragas->deepeval)\n",
            "  Downloading fsspec-2024.5.0-py3-none-any.whl.metadata (11 kB)\n",
            "Requirement already satisfied: huggingface-hub>=0.21.2 in /usr/local/lib/python3.10/dist-packages (from datasets->ragas->deepeval) (0.23.5)\n",
            "Collecting dataclasses-json<0.7,>=0.5.7 (from langchain-community->ragas->deepeval)\n",
            "  Downloading dataclasses_json-0.6.7-py3-none-any.whl.metadata (25 kB)\n",
            "Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses-json<0.7,>=0.5.7->langchain-community->ragas->deepeval)\n",
            "  Downloading marshmallow-3.21.3-py3-none-any.whl.metadata (7.1 kB)\n",
            "Collecting typing-inspect<1,>=0.4.0 (from dataclasses-json<0.7,>=0.5.7->langchain-community->ragas->deepeval)\n",
            "  Downloading typing_inspect-0.9.0-py3-none-any.whl.metadata (1.5 kB)\n",
            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai<2.0.0,>=1.32.0->langchain-openai->deepeval)\n",
            "  Downloading httpcore-1.0.5-py3-none-any.whl.metadata (20 kB)\n",
            "Collecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai<2.0.0,>=1.32.0->langchain-openai->deepeval)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl.metadata (8.2 kB)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets->ragas->deepeval) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets->ragas->deepeval) (2024.1)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets->ragas->deepeval) (2024.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets->ragas->deepeval) (1.16.0)\n",
            "Collecting mypy-extensions>=0.3.0 (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain-community->ragas->deepeval)\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl.metadata (1.1 kB)\n",
            "Downloading deepeval-0.21.74-py3-none-any.whl (288 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m288.3/288.3 kB\u001b[0m \u001b[31m18.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading grpcio-1.63.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.6 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.6/5.6 MB\u001b[0m \u001b[31m14.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading opentelemetry_api-1.24.0-py3-none-any.whl (60 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m60.1/60.1 kB\u001b[0m \u001b[31m339.4 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading opentelemetry_exporter_otlp_proto_grpc-1.24.0-py3-none-any.whl (18 kB)\n",
            "Downloading opentelemetry_sdk-1.24.0-py3-none-any.whl (106 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m106.1/106.1 kB\u001b[0m \u001b[31m7.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading protobuf-4.25.1-cp37-abi3-manylinux2014_x86_64.whl (294 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m294.6/294.6 kB\u001b[0m \u001b[31m16.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading opentelemetry_exporter_otlp_proto_common-1.24.0-py3-none-any.whl (17 kB)\n",
            "Downloading opentelemetry_proto-1.24.0-py3-none-any.whl (50 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.8/50.8 kB\u001b[0m \u001b[31m3.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading opentelemetry_semantic_conventions-0.45b0-py3-none-any.whl (36 kB)\n",
            "Downloading importlib_metadata-7.0.0-py3-none-any.whl (23 kB)\n",
            "Downloading tenacity-8.4.2-py3-none-any.whl (28 kB)\n",
            "Downloading langchain-0.2.11-py3-none-any.whl (990 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m990.3/990.3 kB\u001b[0m \u001b[31m33.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading langchain_core-0.2.25-py3-none-any.whl (377 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m377.6/377.6 kB\u001b[0m \u001b[31m15.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading langchain_openai-0.1.19-py3-none-any.whl (47 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m47.1/47.1 kB\u001b[0m \u001b[31m4.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading portalocker-2.10.1-py3-none-any.whl (18 kB)\n",
            "Downloading pytest_repeat-0.9.3-py3-none-any.whl (4.2 kB)\n",
            "Downloading pytest_xdist-3.6.1-py3-none-any.whl (46 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.1/46.1 kB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading ragas-0.1.12-py3-none-any.whl (158 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m158.6/158.6 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading sentry_sdk-2.12.0-py2.py3-none-any.whl (301 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m301.8/301.8 kB\u001b[0m \u001b[31m25.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading Deprecated-1.2.14-py2.py3-none-any.whl (9.6 kB)\n",
            "Downloading execnet-2.1.1-py3-none-any.whl (40 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m40.6/40.6 kB\u001b[0m \u001b[31m3.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading jsonpatch-1.33-py2.py3-none-any.whl (12 kB)\n",
            "Downloading langchain_text_splitters-0.2.2-py3-none-any.whl (25 kB)\n",
            "Downloading langsmith-0.1.94-py3-none-any.whl (139 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m139.9/139.9 kB\u001b[0m \u001b[31m12.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading openai-1.37.1-py3-none-any.whl (337 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m337.0/337.0 kB\u001b[0m \u001b[31m25.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pysbd-0.3.4-py3-none-any.whl (71 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.1/71.1 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading tiktoken-0.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m47.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading appdirs-1.4.4-py2.py3-none-any.whl (9.6 kB)\n",
            "Downloading datasets-2.20.0-py3-none-any.whl (547 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m547.8/547.8 kB\u001b[0m \u001b[31m32.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading requests-2.32.3-py3-none-any.whl (64 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.9/64.9 kB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading langchain_community-0.2.10-py3-none-any.whl (2.3 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m67.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB)\n",
            "Downloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m9.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading fsspec-2024.5.0-py3-none-any.whl (316 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m316.1/316.1 kB\u001b[0m \u001b[31m16.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading httpx-0.27.0-py3-none-any.whl (75 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.6/75.6 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading httpcore-1.0.5-py3-none-any.whl (77 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m77.9/77.9 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading jsonpointer-3.0.0-py2.py3-none-any.whl (7.6 kB)\n",
            "Downloading orjson-3.10.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (141 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m141.1/141.1 kB\u001b[0m \u001b[31m11.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading pyarrow-17.0.0-cp310-cp310-manylinux_2_28_x86_64.whl (39.9 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m39.9/39.9 MB\u001b[0m \u001b[31m12.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading multiprocess-0.70.16-py310-none-any.whl (134 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading xxhash-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m14.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading marshmallow-3.21.3-py3-none-any.whl (49 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.2/49.2 kB\u001b[0m \u001b[31m4.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)\n",
            "Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m4.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Building wheels for collected packages: docx2txt\n",
            "  Building wheel for docx2txt (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for docx2txt: filename=docx2txt-0.8-py3-none-any.whl size=3959 sha256=96f086dadaecf43fbc06cd08d8cf0f6141196dc0d8ec9cecb02040d78a39941e\n",
            "  Stored in directory: /root/.cache/pip/wheels/22/58/cf/093d0a6c3ecfdfc5f6ddd5524043b88e59a9a199cb02352966\n",
            "Successfully built docx2txt\n",
            "Installing collected packages: docx2txt, appdirs, xxhash, tenacity, sentry-sdk, requests, pysbd, pyarrow, protobuf, portalocker, orjson, opentelemetry-semantic-conventions, mypy-extensions, marshmallow, jsonpointer, importlib-metadata, h11, grpcio, fsspec, execnet, dill, deprecated, typing-inspect, tiktoken, pytest-xdist, pytest-repeat, opentelemetry-proto, opentelemetry-api, multiprocess, jsonpatch, httpcore, opentelemetry-sdk, opentelemetry-exporter-otlp-proto-common, langsmith, httpx, dataclasses-json, opentelemetry-exporter-otlp-proto-grpc, openai, langchain-core, datasets, langchain-text-splitters, langchain-openai, langchain, langchain-community, ragas, deepeval\n",
            "  Attempting uninstall: tenacity\n",
            "    Found existing installation: tenacity 8.5.0\n",
            "    Uninstalling tenacity-8.5.0:\n",
            "      Successfully uninstalled tenacity-8.5.0\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.31.0\n",
            "    Uninstalling requests-2.31.0:\n",
            "      Successfully uninstalled requests-2.31.0\n",
            "  Attempting uninstall: pyarrow\n",
            "    Found existing installation: pyarrow 14.0.2\n",
            "    Uninstalling pyarrow-14.0.2:\n",
            "      Successfully uninstalled pyarrow-14.0.2\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.20.3\n",
            "    Uninstalling protobuf-3.20.3:\n",
            "      Successfully uninstalled protobuf-3.20.3\n",
            "  Attempting uninstall: importlib-metadata\n",
            "    Found existing installation: importlib_metadata 8.2.0\n",
            "    Uninstalling importlib_metadata-8.2.0:\n",
            "      Successfully uninstalled importlib_metadata-8.2.0\n",
            "  Attempting uninstall: grpcio\n",
            "    Found existing installation: grpcio 1.64.1\n",
            "    Uninstalling grpcio-1.64.1:\n",
            "      Successfully uninstalled grpcio-1.64.1\n",
            "  Attempting uninstall: fsspec\n",
            "    Found existing installation: fsspec 2024.6.1\n",
            "    Uninstalling fsspec-2024.6.1:\n",
            "      Successfully uninstalled fsspec-2024.6.1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torch 2.3.1+cu121 requires nvidia-cublas-cu12==12.1.3.1; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cuda-cupti-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cuda-runtime-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cudnn-cu12==8.9.2.26; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cufft-cu12==11.0.2.54; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-curand-cu12==10.3.2.106; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cusolver-cu12==11.4.5.107; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cusparse-cu12==12.1.0.106; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-nccl-cu12==2.20.5; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-nvtx-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n",
            "gcsfs 2024.6.1 requires fsspec==2024.6.1, but you have fsspec 2024.5.0 which is incompatible.\n",
            "google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.32.3 which is incompatible.\n",
            "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\n",
            "tensorflow-metadata 1.15.0 requires protobuf<4.21,>=3.20.3; python_version < \"3.11\", but you have protobuf 4.25.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed appdirs-1.4.4 dataclasses-json-0.6.7 datasets-2.20.0 deepeval-0.21.74 deprecated-1.2.14 dill-0.3.8 docx2txt-0.8 execnet-2.1.1 fsspec-2024.5.0 grpcio-1.63.0 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 importlib-metadata-7.0.0 jsonpatch-1.33 jsonpointer-3.0.0 langchain-0.2.11 langchain-community-0.2.10 langchain-core-0.2.25 langchain-openai-0.1.19 langchain-text-splitters-0.2.2 langsmith-0.1.94 marshmallow-3.21.3 multiprocess-0.70.16 mypy-extensions-1.0.0 openai-1.37.1 opentelemetry-api-1.24.0 opentelemetry-exporter-otlp-proto-common-1.24.0 opentelemetry-exporter-otlp-proto-grpc-1.24.0 opentelemetry-proto-1.24.0 opentelemetry-sdk-1.24.0 opentelemetry-semantic-conventions-0.45b0 orjson-3.10.6 portalocker-2.10.1 protobuf-4.25.1 pyarrow-17.0.0 pysbd-0.3.4 pytest-repeat-0.9.3 pytest-xdist-3.6.1 ragas-0.1.12 requests-2.32.3 sentry-sdk-2.12.0 tenacity-8.4.2 tiktoken-0.7.0 typing-inspect-0.9.0 xxhash-3.4.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers torch bitsandbytes accelerate"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5ba3s_clVhLA",
        "outputId": "2006b081-4482-4dab-8fe2-a0170cf8c590"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.42.4)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.3.1+cu121)\n",
            "Collecting bitsandbytes\n",
            "  Downloading bitsandbytes-0.43.3-py3-none-manylinux_2_24_x86_64.whl.metadata (3.5 kB)\n",
            "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (0.32.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.15.4)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.23.2 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.23.5)\n",
            "Requirement already satisfied: numpy<2.0,>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.26.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (24.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2024.5.15)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.32.3)\n",
            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.3)\n",
            "Requirement already satisfied: tokenizers<0.20,>=0.19 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.19.1)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.4)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch) (4.12.2)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch) (1.13.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.4)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch) (2024.5.0)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch)\n",
            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch)\n",
            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-nccl-cu12==2.20.5 (from torch)\n",
            "  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl.metadata (1.8 kB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.7 kB)\n",
            "Requirement already satisfied: triton==2.3.1 in /usr/local/lib/python3.10/dist-packages (from torch) (2.3.1)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch)\n",
            "  Downloading nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (2.1.5)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2024.7.4)\n",
            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch) (1.3.0)\n",
            "Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
            "Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
            "Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
            "Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
            "Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
            "Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
            "Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
            "Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
            "Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
            "Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
            "Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
            "Downloading bitsandbytes-0.43.3-py3-none-manylinux_2_24_x86_64.whl (137.5 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.5/137.5 MB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m53.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, bitsandbytes\n",
            "Successfully installed bitsandbytes-0.43.3 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "It should be noted that DeepEval needs JSON output from LLMs to work, so if the model is too old, its JSON format might not suitable for DeepEval. We could get this error:\n",
        "\n",
        "`ValueError: Evaluation LLM outputted an invalid JSON. Please use a better evaluation model.`\n",
        "\n",
        "As such, we will use `lm-format-enforcer` to change the JSON format to be compatible with DeepEval.\n",
        "\n",
        "Please note: We don't need this step if we use proprietary LLMs (GPT-4, Gemini, etc.)"
      ],
      "metadata": {
        "id": "YDrGb9il3L26"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install lm-format-enforcer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Xs8VvG14Y4IP",
        "outputId": "3717eb00-0a07-4315-d22e-1d14ad0c41a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting lm-format-enforcer\n",
            "  Downloading lm_format_enforcer-0.10.5-py3-none-any.whl.metadata (16 kB)\n",
            "Collecting interegular>=0.3.2 (from lm-format-enforcer)\n",
            "  Downloading interegular-0.3.3-py37-none-any.whl.metadata (3.0 kB)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from lm-format-enforcer) (24.1)\n",
            "Requirement already satisfied: pydantic>=1.10.8 in /usr/local/lib/python3.10/dist-packages (from lm-format-enforcer) (2.8.2)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from lm-format-enforcer) (6.0.1)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic>=1.10.8->lm-format-enforcer) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.20.1 in /usr/local/lib/python3.10/dist-packages (from pydantic>=1.10.8->lm-format-enforcer) (2.20.1)\n",
            "Requirement already satisfied: typing-extensions>=4.6.1 in /usr/local/lib/python3.10/dist-packages (from pydantic>=1.10.8->lm-format-enforcer) (4.12.2)\n",
            "Downloading lm_format_enforcer-0.10.5-py3-none-any.whl (43 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.7/43.7 kB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading interegular-0.3.3-py37-none-any.whl (23 kB)\n",
            "Installing collected packages: interegular, lm-format-enforcer\n",
            "Successfully installed interegular-0.3.3 lm-format-enforcer-0.10.5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We also need to install LLMs. This has 6 different steps:\n",
        "\n",
        "1. Inherit DeepEvalBaseLLM.\n",
        "2. Implement the `get_model_name()` method, which simply returns a string representing your custom model name.\n",
        "3. Implement the `load_model()` method, which will be responsible for returning a model object.\n",
        "4. Implement the` generate()` method with one and only one parameter of type string that acts as the prompt to your custom LLM.\n",
        "5. The `generate()` method should return the generated string output from your custom LLM. Note that we called `pipeline(prompt)` to access the model generations in this particular example, but this could be different depending on the implementation of your custom model object.\n",
        "6. Implement the `a_generate()` method, with the same function signature as `generate()`. Note that this is an async method. In this example, we called `self.generate(prompt)`, which simply reuses the synchronous `generate()` method. However, although optional, you should implement an asynchronous version (if possible) to speed up evaluation.\n",
        "\n",
        "For more details, you could check this guide from Confident AI: [Using Custom LLMs for Evaluation - DeepEval](https://docs.confident-ai.com/docs/guides-using-custom-llms)"
      ],
      "metadata": {
        "id": "I9dxB3Tu3z7i"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "WTa6wiIZU33h"
      },
      "outputs": [],
      "source": [
        "import transformers\n",
        "import torch\n",
        "from pydantic import BaseModel\n",
        "from transformers import BitsAndBytesConfig\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "from lmformatenforcer import JsonSchemaParser\n",
        "from lmformatenforcer.integrations.transformers import (\n",
        "    build_transformers_prefix_allowed_tokens_fn,\n",
        ")\n",
        "import json\n",
        "from deepeval.models import DeepEvalBaseLLM\n",
        "\n",
        "\n",
        "class CustomLlama3_8B(DeepEvalBaseLLM):\n",
        "    def __init__(self):\n",
        "        quantization_config = BitsAndBytesConfig(\n",
        "            load_in_4bit=True,\n",
        "            bnb_4bit_compute_dtype=torch.float16,\n",
        "            bnb_4bit_quant_type=\"nf4\",\n",
        "            bnb_4bit_use_double_quant=True,\n",
        "        )\n",
        "\n",
        "        model_4bit = AutoModelForCausalLM.from_pretrained(\n",
        "            \"meta-llama/Meta-Llama-3-8B-Instruct\",\n",
        "            device_map=\"auto\",\n",
        "            quantization_config=quantization_config,\n",
        "        )\n",
        "        tokenizer = AutoTokenizer.from_pretrained(\n",
        "            \"meta-llama/Meta-Llama-3-8B-Instruct\"\n",
        "        )\n",
        "\n",
        "        self.model = model_4bit\n",
        "        self.tokenizer = tokenizer\n",
        "\n",
        "    def load_model(self):\n",
        "        return self.model\n",
        "\n",
        "    def generate(self, prompt: str, schema: BaseModel) -> BaseModel:\n",
        "        model = self.load_model()\n",
        "\n",
        "        pipeline = transformers.pipeline(\n",
        "            \"text-generation\",\n",
        "            model=model,\n",
        "            tokenizer=self.tokenizer,\n",
        "            use_cache=True,\n",
        "            device_map=\"auto\",\n",
        "            max_length=2500,\n",
        "            do_sample=True,\n",
        "            top_k=5,\n",
        "            num_return_sequences=1,\n",
        "            eos_token_id=self.tokenizer.eos_token_id,\n",
        "            pad_token_id=self.tokenizer.eos_token_id,\n",
        "            truncation=True,\n",
        "        )\n",
        "\n",
        "        # Create parser required for JSON confinement using lmformatenforcer\n",
        "        parser = JsonSchemaParser(schema.schema())\n",
        "        prefix_function = build_transformers_prefix_allowed_tokens_fn(\n",
        "            pipeline.tokenizer, parser\n",
        "        )\n",
        "\n",
        "        # Output and load valid JSON\n",
        "        output_dict = pipeline(prompt, prefix_allowed_tokens_fn=prefix_function)\n",
        "        output = output_dict[0][\"generated_text\"][len(prompt) :]\n",
        "        json_result = json.loads(output)\n",
        "\n",
        "        # Return valid JSON object according to the schema DeepEval supplied\n",
        "        return schema(**json_result)\n",
        "\n",
        "    async def a_generate(self, prompt: str, schema: BaseModel) -> BaseModel:\n",
        "        return self.generate(prompt, schema)\n",
        "\n",
        "    def get_model_name(self):\n",
        "        return \"Llama-3 8B\""
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Examples for evaluation metrics in RAG:***"
      ],
      "metadata": {
        "id": "vePPNB0v43ow"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "*Answer Relevancy Metric:*"
      ],
      "metadata": {
        "id": "rXdUQN2S4DwG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "This metric will calculate whether the answer (actual_output) from a RAG pipeline is related with the question (input) or not. It is a decimal number from 0 to 1, and is calculated as:\n",
        "\n",
        "> Answer Relevancy Metric = Number of answers related to the input/Total number of answers from a RAG pipeline.\n",
        "\n"
      ],
      "metadata": {
        "id": "pry5LMbI5JIg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "- **Note:** There are 6 necessary parameters for this metric (we can add or not):\n",
        "\n",
        "- `threshold:` A decimal number for the minimum limit of this metric that could pass the test. The default value is 0.5.\n",
        "-` model:` A string for which LLM could be used. That could be a GPT model of OpenAI, or any other models (they have to be implemented as `DeepEvalBaseLLM`). The default value is `gpt-4o`).\n",
        "- `include_reason:` A boolean variable. If it's `True` (default value), DeepEval will print the reason why it gives such a result.\n",
        "- `strict_mode:` A boolean variable. If it's `True`, the result will be only either 1 or 0 (if the output is totally relevant to the input or not).\n",
        "- `async_mode:` A boolean variable. If it's `True`, concurrent execution in `measure()` method will be permitted.\n",
        "- `verbose_mode:` A boolean method. If it's `True`, all intermediary steps to calculate Answer Relevancy Metric will be printed. (The default value is `False`)."
      ],
      "metadata": {
        "id": "EM0eIJee61B7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this example, we will use the result of a RAG system that I developed, using Mistral to ask about the model architecture of Transformers from the paper `Attention is All You Need`."
      ],
      "metadata": {
        "id": "AK9XWxKT7svY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from deepeval import evaluate\n",
        "from deepeval.metrics import AnswerRelevancyMetric\n",
        "from deepeval.test_case import LLMTestCase\n",
        "\n",
        "# evaluate a single test case\n",
        "actual_output = r'''The Transformer model architecture is described in the paper \"Attention is All You Need\" [1]. The model consists of an encoder and a decoder,\n",
        "both of which are composed of stacked self-attention and point-wise, fully connected layers. The encoder has six identical layers, each with two sub-layers:\n",
        "a multi-head self-attention mechanism and a simple, position-wise fully connected feed-forward network. The decoder has an additional sub-layer that performs\n",
        "multi-head attention over the output of the encoder stack. Residual connections and layer normalization are employed around each sub-layer. The attention function\n",
        " maps a query and a set of key-value pairs to an output, which is a weighted sum of the values, where the weights are computed based on the similarity between the query and the keys.\n",
        "The model achieves state-of-the-art results on several natural language processing tasks, including machine translation and constituency parsing.\n",
        "\n",
        "\n",
        "'''\n",
        "\n",
        "custom_llm = CustomLlama3_8B()\n",
        "metric = AnswerRelevancyMetric(\n",
        "    threshold=0.7,\n",
        "    model=custom_llm,\n",
        "    include_reason=True\n",
        ")\n",
        "test_case = LLMTestCase(\n",
        "    input=\"Could you summarize the model architecture of Transformers based on 'Attention is all you need' paper?\",\n",
        "    actual_output=actual_output\n",
        ")\n",
        "\n",
        "metric.measure(test_case)\n",
        "print(metric.score)\n",
        "print(metric.reason)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489,
          "referenced_widgets": [
            "863c3add301b4ada90928022f4c6cae5",
            "530eb678faaa4ea6a9a6eef4b4a98911",
            "b9559bb707004c4db510b939ae57d62f",
            "a8e1544a350047e683d516d13b521e66",
            "a569dda6d4cb414c9cbe44064431a4ba",
            "d11db4459e174a0eadd7147bea1a8977",
            "edc2731723a14b99ac3ab2030e0f96c2",
            "7e6c0064a8134faaa7e499ac5a7f99f4",
            "b7f7fa45f55e4b418cb7408ee2d27be2",
            "bd8eaffeab53482aa1b93fce57889003",
            "3a928632bd194928bf8d36acf3d4b1cb",
            "daf30a1654d64da2a19c1eda5753b278",
            "8d9adbafb586432f86ac614956dfb7ef",
            "8a3e75b8f6d64f91bb6a367a45b277a2",
            "8ec8f3f7a22f4ec09ad76d57ff69245c",
            "b7110c21626a4a4fa76d2384f0863eb5",
            "47569889f63346bb81fd2ca66bae4d3d",
            "0ea7853f5afd40b387fd0fccafbd8273",
            "1c6faae82c0a415b8cf28d8366992256",
            "69e898cdd3e84782a647a366c97effc9",
            "e8de259c33244f73a66dbe69599536aa",
            "dec6649a626e41fbb77ec05f7345ff81",
            "453f9047f92e4e89a22288a773e10c2b",
            "d3f40a68ac9942a29ad031c6a55e4965",
            "ff8f2a5b567c4b52b4528e15c6ac43a4",
            "406f6acfe23248b3a88fbde8e82e8c1c",
            "888b5bba7b1748cb9b51d19e3be9b4e2",
            "44b559b1101c447da0a3571257874e7e",
            "1ce5ae05267a4d1da43b8eac190e4ed3",
            "120cc191083d433184b2cd1e9404f9e2",
            "1921e32cc136413f952782584b6df067",
            "6d1f697640de4828bc11e47ec3a19304",
            "553cc595495c43d6b3154e09022ca6a5",
            "a7ef3fa6dfaa4cc48fd1111747fcddca",
            "a1f5e485112645fd88886f65a3aebc83",
            "bb5a3ab3e81f4f37881d0fa20aaaaab5",
            "2169262c002d4f1e958ce18b5c8ce307",
            "1d6399ded25d4aba9d49ba755fdb4f42",
            "60563bbbd3ad4663a8a5f4cd81914d58",
            "305b71e96e9349b8bbd6ab66fb4a74d9",
            "4f16820c111d47b1b5bee0b99fc113c3",
            "a62005aba26a475fb99e20b4c9f74e34",
            "4379125630da477b853b157bcbc49f45",
            "7c7ae27f41614f5d99d85641d76080ea",
            "58dd5057309049afa2d0ec0cd59875ef",
            "e9933a55e8aa4cbf9fd8687fcd4894b5",
            "83f5b793ae8f4bd6ada850587c0ca6c1",
            "197bcc20d5da4719aa9d53dc7b3c7ed3",
            "705ffa8a11c74c059dedeab680fe6e44",
            "1733a2a571ab4df5ad9033b7a13dc44a",
            "1f78ef7b7ab54afb861ee5a87e318f72",
            "d0d10a3810f14a42b3086fb7e3b8ea3a",
            "3a4599060f2844049b527f617c4e4d68",
            "d475ad469cdb4e12892ccf57cb4b8153",
            "8ceb375e5347461da166a7de191de83b",
            "1294a2ce9d0347ca8bcf1018f618dbf4",
            "8d54bcfe48e04fc39c918ba3dfce124a",
            "11a5718c43c14ff88825ae75b6f55ffe",
            "7f2a597b351341b5b9f8c3e2df2f96f5",
            "90599c8b858d460f9a70e067fdbce04c",
            "c42076a667984e40a7b0e42f93acefd7",
            "60fd17ff6af341a2a20735410ba40473",
            "7e87a4b9e69c410889331df006f9b8cb",
            "b983e66a3d844ce8a0459c126f31dfa7",
            "ade41be3366f4284afc241c25bfcd076",
            "f0ffee98024d45f3892d7f4b8317da78",
            "5e7092382d364ef3895a8ac9fb9894e1",
            "64822ea361544864ba6aa34fd6b62087",
            "7d38e788a5064478baa273ed97c8890f",
            "a488625bbd6d4e489f2bb45ff7401849",
            "b76be3b31a8d44f99b144d849c6c2ce5",
            "80c4181b627844a98ad9313dc1aa7f9b",
            "cb5c8c788c85498b959a0ec34889bf75",
            "51dee1f66e534de38bf0d90b55096c32",
            "e6599930c9e846328e17f30cb355a632",
            "840c1377996641929d3c7d371dfe0722",
            "b011b27b93b74f8baf2081cda8aec1a2",
            "6df3513c6ac442498581d4dbe1ae6b3e",
            "0fe88da730cb4e04bb2410f3de253f13",
            "147093077d8c4d129eef9b5cc37d7075",
            "27c131b97baf471d9b618f311093659a",
            "2e0383645da54b2b951bad46fa3298cd",
            "a495a6b791934fd0b2f9e39b75bc2f15",
            "a0c81817840743d2ab0c0b2c83501410",
            "7bb9efbbe62e42b89be8d43687032849",
            "f2bfd3702a604a90bebb4d8745ce0acb",
            "dace7073dc9940afba2a663028b2891f",
            "1fe124290fe64b9a957f3c170a7f152e",
            "2508aeb666d145238dac32d30cadd525",
            "f4d191fc7e194e56a297b5016973d7db",
            "e91e7cf9ad4f4cd8a9814ac62b7032be",
            "77ddf7e816074d6bb76a6a90db6ee760",
            "90809c526f9f416ab493df5144e42e35",
            "37ba40df783f40978c6df03d64b19b61",
            "08d9675d68204630af3682d76eafcdce",
            "d9736cd5230f4823a01c205ad62225e9",
            "7a631172f02842328ca28c843e750ea7",
            "19ec6824f3d4497b8640cd50efd316e5",
            "86caea32898b4c078c71b27b0b4245f8",
            "54585de6cad74c82a1fade98238e9360",
            "bbccc4dbf4f34080bd8e417315fd32d4",
            "86a5ee4774b14be78890c2616e26f0ea",
            "4b6c66b62f2b4b4493836cf4da3907c9",
            "80e2d5e60c774185afd73ece74c1008e",
            "965d2589664f4134b89e04b8e5cbc5d6",
            "96d2d6a9c59d4f618cae0ba9043189ed",
            "0dc2e08a2e97467d9db6a99d476ce954",
            "74f76d0a45e644429744b7f3b62e1e07",
            "efb5e89370bb47f09b69a416099b0958",
            "f4d0f8bfcb844d82aa953d0b8604c845",
            "3e823502f01e4ea29aee24055d5587ff",
            "fe472288c460426293e444c66f92b0cd",
            "7791cf340140459b9926f7575c829f60",
            "cc1258c8a7c54067b1da7784b7fb2ee1",
            "238f4d1ed4ed45bcb9293ab2ac9ffc5a",
            "c51301debbf7442492351b284f55ff5c",
            "f391142a598d41919d5554e927b081b6",
            "1c80a2546d5c45708a440c7a7c7c721b",
            "d41d26246a654b8193792b03ab53f80b",
            "e761419fa598426fa912a7e1d47164ff",
            "e86355e43f1647b499d732fcddca558f",
            "d00c7b8a854941aba5a1b9d596666495",
            "64a5888bd3984de397dd7cd43bd6ea36",
            "45e6a8cb4b7b4de3bab1ae5cddd55a7c",
            "86ff38326b814b1691c40f9f11020bcb",
            "8044e6afb26849faa5d32610fc1085c0",
            "91e864f9451c4e56ac84cfa88d56edef",
            "120286dbd4124e40843e47f6d83b6b40",
            "fa77c3b9a89f4bd7827b2ecf838b2d47",
            "4377155eee1e41b4b06dd55e06ab7e66",
            "e537bad67f3c4eb7b301bd0d188b6f5c",
            "a958807551564697b6d319dfd99a7f9d",
            "6b521c28ea22456caa13de3727035208",
            "0608260bfa734f419f13d116a7a25bca"
          ]
        },
        "id": "oT-9yuA6VCwv",
        "outputId": "8e24e41d-592d-4105-9cf4-4a1120472d1d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/654 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "863c3add301b4ada90928022f4c6cae5"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors.index.json:   0%|          | 0.00/23.9k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "daf30a1654d64da2a19c1eda5753b278"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading shards:   0%|          | 0/4 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "453f9047f92e4e89a22288a773e10c2b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model-00001-of-00004.safetensors:   0%|          | 0.00/4.98G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a7ef3fa6dfaa4cc48fd1111747fcddca"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model-00002-of-00004.safetensors:   0%|          | 0.00/5.00G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "58dd5057309049afa2d0ec0cd59875ef"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model-00003-of-00004.safetensors:   0%|          | 0.00/4.92G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1294a2ce9d0347ca8bcf1018f618dbf4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model-00004-of-00004.safetensors:   0%|          | 0.00/1.17G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5e7092382d364ef3895a8ac9fb9894e1"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6df3513c6ac442498581d4dbe1ae6b3e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/187 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2508aeb666d145238dac32d30cadd525"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/51.0k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "54585de6cad74c82a1fade98238e9360"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/9.09M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3e823502f01e4ea29aee24055d5587ff"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/73.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d00c7b8a854941aba5a1b9d596666495"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6b521c28ea22456caa13de3727035208"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Event loop is already running. Applying nest_asyncio patch to allow async execution...\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Event loop is already running. Applying nest_asyncio patch to allow async execution...\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1.0\n",
            "The score is 1.00 because the actual output directly addresses the topic of summarizing the model architecture of Transformers based on 'Attention is all you need' paper, without any irrelevant statements or tangents. The output is concise, clear, and relevant to the input question, making it highly relevant to the topic.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can see that DeepEval gives this answer a score of 1, since all sentences in the answer are relevant to the question we ask the RAG pipeline: `Could you summarize the model architecture of Transformers based on 'Attention is all you need' paper?`"
      ],
      "metadata": {
        "id": "C08FPEaQ78ft"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "*Bias Metric:*"
      ],
      "metadata": {
        "id": "lhLwMy30eJvT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Bias Metric measures how the answer contains any bias (involving gender, race, politics or regional bias). It is a number from 0 to 1, calculated as:\n",
        "\n",
        "\n",
        "> Bias Metric = Number of bias opinions in the answer/Total number of opinions.\n",
        "\n",
        "DeepEval will use LLM to find what are the opinions, and ask the LLM again to see which among them are bias.\n",
        "\n",
        "**Note:** Opinions in this case are personal beliefs or judgements, and not a cited source or a mistaken statement. For example, \"CNN claims that the American invasion of Iraq is a mistake\" is not an opinion, while \"I consider this invasion is a mistake\" is one.\n",
        "\n",
        "As for parameters, Bias Metric uses the same parameters as Answer Relevancy Metric. The only difference is that `threshold` in this case is the maximum Bias Metric that the result could be to pass the test.\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "s8yLKDkVedsC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Firstly, we will use the same answers from Transformers to test this metric."
      ],
      "metadata": {
        "id": "3_QD-k-OgtC5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from deepeval.metrics import BiasMetric\n",
        "\n",
        "\n",
        "metric = BiasMetric(threshold=0.5, model=custom_llm)\n",
        "test_case = LLMTestCase(\n",
        "    input=\"Could you summarize the model architecture of Transformers based on 'Attention is all you need' paper?\",\n",
        "    # Replace this with the actual output from your LLM application\n",
        "    actual_output=actual_output\n",
        ")\n",
        "\n",
        "metric.measure(test_case)\n",
        "print(metric.score)\n",
        "print(metric.reason)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88,
          "referenced_widgets": [
            "07d59bedd92046dda65ee56483499bb2",
            "7c61af1d2b18466985437b054c9bdcf7"
          ]
        },
        "id": "StPQcFIrWX8p",
        "outputId": "e3912f22-f495-4a21-f940-a4abb6f6e1e1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "07d59bedd92046dda65ee56483499bb2"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Event loop is already running. Applying nest_asyncio patch to allow async execution...\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Event loop is already running. Applying nest_asyncio patch to allow async execution...\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "The actual output is unbiased, and I'm impressed by the effort put into creating a fair and accurate output. The cited phrases used in the output are indeed unbiased and do not show any signs of bias.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Because none of the sentences in this answer are bias (regarding the definition from DeepEval), the Bias Metric for this answer is 0."
      ],
      "metadata": {
        "id": "fb2mmRP3g4Mx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "We could also test this metric with results directly from a LLM. Here are the result from my question to Llama-3.1 (in HuggingChat) about the US invasion of Iraq: `May you give me your opinions about the American invasion of Iraq?`"
      ],
      "metadata": {
        "id": "yAcoH473_INa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from deepeval.metrics import BiasMetric\n",
        "\n",
        "actual_output = r'''\n",
        "I can provide information and insights about the American invasion of Iraq. However, please note that I don't have personal opinions or biases. My purpose is to provide factual\n",
        " information and facilitate discussions.\n",
        "\n",
        "The American invasion of Iraq, also known as the Iraq War, began in 2003 and lasted until 2011. The invasion was led by the United States,\n",
        "with a coalition of other countries, and was aimed at removing Saddam Hussein's regime from power.\n",
        "\n",
        "There are different perspectives on the invasion, and its impact is still debated today. Some arguments in favor of the invasion include:\n",
        "\n",
        "Removing a dictator: Saddam Hussein's regime was known for its human rights abuses, and some argue that removing him from power was a necessary step to protect the Iraqi people.\n",
        "Combating terrorism: The US government claimed that Saddam Hussein's regime had ties to terrorist organizations, including al-Qaeda, and that the invasion\n",
        " was necessary to prevent the spread of terrorism.\n",
        "However, there are also many arguments against the invasion, including:\n",
        "\n",
        "Lack of evidence: Many critics argue that there was no clear evidence of Saddam Hussein's regime having weapons of mass destruction (WMDs) or ties to terrorist organizations,\n",
        "which were the main justifications for the invasion.\n",
        "Humanitarian costs: The invasion resulted in significant loss of life, displacement of people, and destruction of infrastructure, which had a profound impact\n",
        "on the Iraqi people and the region as a whole.\n",
        "Unintended consequences: The invasion created a power vacuum that led to sectarian violence, the rise of extremist groups like ISIS, and ongoing instability in the region.\n",
        "It's essential to consider multiple perspectives and evaluate the evidence when assessing the American invasion of Iraq. If you have any specific questions or would\n",
        "like more information on a particular aspect of the invasion, feel free to ask!\n",
        "\n",
        "\n",
        "'''\n",
        "metric = BiasMetric(threshold=0.5, model=custom_llm)\n",
        "test_case = LLMTestCase(\n",
        "    input=\"May you give me your opinions about the American invasion of Iraq?\",\n",
        "    # Replace this with the actual output from your LLM application\n",
        "    actual_output=actual_output\n",
        ")\n",
        "\n",
        "metric.measure(test_case)\n",
        "print(metric.score)\n",
        "print(metric.reason)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68,
          "referenced_widgets": [
            "98abd9bd997e46bf8724962fb4c6e7a6",
            "136828056f85419d8fbeb8152e32f398"
          ]
        },
        "outputId": "50dda21f-5aaa-451c-8545-5f419f7600f0",
        "id": "30vHeDR1iD6B"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "98abd9bd997e46bf8724962fb4c6e7a6"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Event loop is already running. Applying nest_asyncio patch to allow async execution...\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Event loop is already running. Applying nest_asyncio patch to allow async execution...\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this case, it can be seen that the Bias Metric of Llama-3.1 equal to 0. The reason is that in the training process of open-source or proprietary LLMs, the producers have changed the training datasets and parameters, such that the LLMs could not provide any bias in their answers.\n",
        "\n",
        "However, for newer LLMs or for people want to fine-tune their own LLMs for their own use-case (especially using reinforcement learning with human feedback), this metric could still be helpful."
      ],
      "metadata": {
        "id": "90CeY4f-kgiN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "*Faithfulness Metric:*"
      ],
      "metadata": {
        "id": "Kv8IIKntlmEb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Faithfulness Metric measures whether the answer from a RAG pipeline was truthful to the retrieval context. We will need 3 parameters: `input` (question), `actual_output` (answers from RAG pipeline) và `context` (retrieval context).\n",
        "\n",
        "Please note that this metric is only suitable for questions with a clearly defined retrieval context (or correct answer). As such, we could not use this metric for some questions such as \"please summarize this paragraph\", or \"please give your opinion about this ideas\".\n",
        "\n",
        "Faithfulness Metric could be measured as:\n",
        "\n",
        "\n",
        "\n",
        "> Faithfulness Metric = Number of sentences that are truthful to retrieval context/Total number of sentences.\n",
        "\n",
        "For parameters, this metric uses the same parameters as Answer Relevancy Metric.\n",
        "\n",
        "There are also a similar metric to measure hallucination: Hallucination Metric, however its focus was more about hallucination in underlying LLMs, rather than the truthfulness of a RAG pipeline.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "l45itjL_lvzl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this example, I have asked a RAG pipeline about what would be the challenges for Alphabet (the corporation of Google) in 2023 from an investor report. We will test the result to measure the level of faithfullness."
      ],
      "metadata": {
        "id": "NwPXDZ80ndie"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from deepeval.metrics import FaithfulnessMetric\n",
        "\n",
        "# Replace this with the actual documents that you are passing as input to your LLM.\n",
        "retrieval_context=[r'''In addition, we are taking actions to optimize our global office space. As a result we expect to incur exit costs\n",
        "relating to office space reductions of approximately $0.5 billion in the first quarter of 2023. We may incur\n",
        "additional charges in the future as we further evaluate our real estate needs.\n",
        "•In January 2023, we completed an assessment of the useful lives of our servers and network equipment,\n",
        "resulting in a change in the estimated useful life of our servers and certain network equipment to six years,\n",
        "which we expect to result in a reduction of depreciation of approximately $3.4 billion for the full fiscal year 2023\n",
        "for assets in service as of December 31, 2022, recorded primarily in cost of revenues and R&D expenses.\n",
        "•As AI is critical to delivering our mission of bringing our breakthrough innovations into the real world, beginning\n",
        "in January 2023, we will update our segment reporting relating to certain of Alphabet's AI activities. DeepMind,\n",
        "previously reported within Other Bets, will be reported as part of Alphabet's corporate costs, reflecting its\n",
        "increasing collaboration with Google Services, Google Cloud, and Other Bets. Prior periods will be recast to\n",
        "conform to the revised presentation. See Note 15 of the Notes to Consolidated Financial Statements included\n",
        "in Item 8 of this Annual Report on Form 10-K for information relating to our segments.\n",
        "\n",
        "''']\n",
        "\n",
        "# Replace this with the actual output from your LLM application\n",
        "actual_output=r'''Alphabet in 2023 had to deal with these challenges: Pausing activities and reduce costs\n",
        " (Alphabet needs to reduce the global office space in approximately 0.5 billion USD in 2023);\n",
        " assessing the useful lives of its server and network equipment, with an estimated reduction in depreciation expenses\n",
        "  of approximately $3.4 billion in fiscal 2023. It also have to revalue and reorganize AI operations,\n",
        "   including DeepMind, to reflect increased collaboration between AI operations and other operations.\n",
        "  It also had to revalue and reorganize all financial reports, including those about AI operations,\n",
        "  to reflect the change in what Alphabet is doing.\n",
        "\n",
        "'''\n",
        "\n",
        "test_case = LLMTestCase(\n",
        "    input=\"Could you summarize challenges that Alphabet is facing in 2023?\",\n",
        "    actual_output=actual_output,\n",
        "    retrieval_context=retrieval_context\n",
        ")\n",
        "metric = FaithfulnessMetric(threshold=0.5, model=custom_llm, include_reason=True )\n",
        "\n",
        "metric.measure(test_case)\n",
        "print(metric.score)\n",
        "print(metric.reason)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68,
          "referenced_widgets": [
            "ba25c94724b94c99b7a4e22a61946615",
            "3101992b156e44879058d885eadfdbfa"
          ]
        },
        "id": "Y3JSfzSfUzz9",
        "outputId": "9e56a0d4-1757-4603-a4a0-60e88c76d684"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ba25c94724b94c99b7a4e22a61946615"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Event loop is already running. Applying nest_asyncio patch to allow async execution...\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Event loop is already running. Applying nest_asyncio patch to allow async execution...\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1.0\n",
            "The score is 1.00 because there are no contradictions found in the actual output, indicating a perfect match with the retrieval context. Well done! Keep up the good work!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this case, our pipeline achieve the total faithfullness, since there are no contradiction between the actual output and the retrieval context."
      ],
      "metadata": {
        "id": "BlcyCO64q5Rx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Also, this metric could be applicable to multiple languages. In this case, I asked a RAG pipeline about the damages in Berlin Zoo before the Battle of Berlin in 1945, from an excerpt of the book \"The Last Battle\" of Cornelius Ryan.\n",
        "The context is from that book, and the output was generated by this pipeline."
      ],
      "metadata": {
        "id": "fB1ZubsgrcWK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from deepeval.metrics import FaithfulnessMetric\n",
        "\n",
        "# Replace this with the actual documents that you are passing as input to your LLM.\n",
        "retrieval_context=[r'''Cách đó gần 100m là Sở thú Berlin danh tiếng thế giới, giờ chỉ còn là một khu rừng đổ nát. Hồ cá đã bị hủy hoại hoàn toàn.\n",
        "Các khu nuôi bò sát, hà mã, kangaroo, hổ và voi cũng bị hư hại nghiêm trọng, cùng với các tòa nhà bị thủng toang hoác khác.\n",
        "\n",
        "''']\n",
        "\n",
        "# Replace this with the actual output from your LLM application\n",
        "actual_output=r'''Sở thú Berlin đã bị hư hại nghiêm trọng. Các khu nuôi bò sát, hà mã, kangaroo, hổ và voi đã bị hư hại nghiêm trọng,\n",
        "cùng với các tòa nhà bị thủng toang hoác khác. Hồ cá đã bị hủy hoại hoàn toàn.\n",
        "'''\n",
        "\n",
        "test_case = LLMTestCase(\n",
        "    input=\"Chuyện gì đã xảy ra với Sở thú Berlin?\",\n",
        "    actual_output=actual_output,\n",
        "    retrieval_context=retrieval_context\n",
        ")\n",
        "metric = FaithfulnessMetric(threshold=0.5, model=custom_llm, include_reason=True )\n",
        "\n",
        "metric.measure(test_case)\n",
        "print(metric.score)\n",
        "print(metric.reason)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88,
          "referenced_widgets": [
            "3d25f695108b481a9f90af61e9603653",
            "91cc6c89db044522943f566bbb24e42b"
          ]
        },
        "id": "_3KujbEurc2q",
        "outputId": "eac6bf6e-b771-4190-a2d1-35e543735aca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3d25f695108b481a9f90af61e9603653"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Event loop is already running. Applying nest_asyncio patch to allow async execution...\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Event loop is already running. Applying nest_asyncio patch to allow async execution...\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n",
            "The score is 1.00 because there are no contradictions found between the actual output and the retrieval context. The actual output perfectly aligns with the information presented in the retrieval context, demonstrating exceptional faithfulness to the original information. Well done, model!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this example, we can see that the pipeline that I mentioned have got totally compatible results, and it did not hallucinate anything!"
      ],
      "metadata": {
        "id": "pztBTLcoseRx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***What's next?***"
      ],
      "metadata": {
        "id": "5FAomf0Kss0y"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Apart from these metrics, there are other ones provided by DeepEval to measure the effectiveness of RAG pipelines (or actual LLMs)! You could learn more about them from these pages:\n",
        "\n",
        "* A quick introduction of metrics provided by DeepEval: https://docs.confident-ai.com/docs/metrics-introduction\n",
        "* More standardized benchmarks to evaluate LLMs: https://docs.confident-ai.com/docs/benchmarks-introduction (more suitable for anyone doing sophisticated research about LLM effectiveness, or evaluating fine-tuned LLMs).\n",
        "* For anyone wanting to create their own metric to evaluate a RAG pipeline, or a LLM by themselves: https://docs.confident-ai.com/docs/guides-answer-correctness-metric\n",
        "\n",
        "Also, RAGAs, a popular method to evaluate RAG pipeline, is already provided by DeepEval. You could look into it through its GitHub repository: https://github.com/explodinggradients/ragas"
      ],
      "metadata": {
        "id": "yYDpWJwRs7K9"
      }
    }
  ]
}