diff --git a/site/en/gemma/docs/get_started.ipynb b/site/en/gemma/docs/keras_inference.ipynb
similarity index 95%
rename from site/en/gemma/docs/get_started.ipynb
rename to site/en/gemma/docs/keras_inference.ipynb
index d1cfe88ac..f32ae96e1 100644
--- a/site/en/gemma/docs/get_started.ipynb
+++ b/site/en/gemma/docs/keras_inference.ipynb
@@ -39,16 +39,16 @@
       "source": [
         "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
         "  <td>\n",
-        "    <a target=\"_blank\" href=\"https://ai.google.dev/gemma/docs/get_started\"><img src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" />View on ai.google.dev</a>\n",
+        "    <a target=\"_blank\" href=\"https://ai.google.dev/gemma/docs/keras_inference\"><img src=\"https://ai.google.dev/static/site-assets/images/docs/notebook-site-button.png\" height=\"32\" width=\"32\" />View on ai.google.dev</a>\n",
         "  </td>\n",
         "    <td>\n",
-        "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/gemma/docs/get_started.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
+        "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/gemma/docs/keras_inference.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
         "  </td>\n",
         "  <td>\n",
-        "    <a target=\"_blank\" href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/google/generative-ai-docs/main/site/en/gemma/docs/get_started.ipynb\"><img src=\"https://ai.google.dev/images/cloud-icon.svg\" width=\"40\" />Open in Vertex AI</a>\n",
+        "    <a target=\"_blank\" href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/google/generative-ai-docs/main/site/en/gemma/docs/keras_inference.ipynb\"><img src=\"https://ai.google.dev/images/cloud-icon.svg\" width=\"40\" />Open in Vertex AI</a>\n",
         "  </td>\n",
         "  <td>\n",
-        "    <a target=\"_blank\" href=\"https://github.com/google/generative-ai-docs/blob/main/site/en/gemma/docs/get_started.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
+        "    <a target=\"_blank\" href=\"https://github.com/google/generative-ai-docs/blob/main/site/en/gemma/docs/keras_inference.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
         "  </td>\n",
         "</table>"
       ]
@@ -235,7 +235,7 @@
         "id": "XrAWvsU6pI0E"
       },
       "source": [
-        "`from_preset` instantiates the model from a preset architecture and weights. In the code above, the string `\"gemma_2b_en\"` specifies the preset architecture: a Gemma model with 2 billion parameters.\n"
+        "The `GemmaCausalLM.from_preset()` function instantiates the model from a preset architecture and weights. In the code above, the string `\"gemma_2b_en\"` specifies the preset the Gemma 2B model with 2 billion parameters. Gemma models with [7B, 9B, and 27B parameters](/gemma/docs/get_started#models-list) are also available. You can find the code strings for Gemma models in their **Model Variation** listings on [Kaggle](https://www.kaggle.com/models/google/gemma).\n"
       ]
     },
     {
@@ -244,7 +244,7 @@
         "id": "Ij73k0PfUhjE"
       },
       "source": [
-        "Note: A Gemma model with 7 billion parameters is also available. To run the larger model in Colab, you need access to the premium GPUs available in paid plans. Alternatively, you can perform [distributed tuning on a Gemma 7B model](https://ai.google.dev/gemma/docs/distributed_tuning) on Kaggle or Google Cloud."
+        "Note: To run the larger models in Colab, you need access to the premium GPUs available in paid plans. Alternatively, you can perform inferences using Kaggle notebooks or Google Cloud projects.\n"
       ]
     },
     {
@@ -588,7 +588,7 @@
   "metadata": {
     "accelerator": "GPU",
     "colab": {
-      "name": "get_started.ipynb",
+      "name": "keras_inference.ipynb",
       "toc_visible": true
     },
     "google": {