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IBM Granite - Wikipedia (function(){var className="client-js vector-feature-language-in-header-enabled vector-feature-language-in-main-page-header-disabled vector-feature-sticky-header-disabled vector-feature-page-tools-pinned-disabled vector-feature-toc-pinned-clientpref-1 vector-feature-main-menu-pinned-disabled vector-feature-limited-width-clientpref-1 vector-feature-limited-width-content-enabled vector-feature-custom-font-size-clientpref-1 vector-feature-appearance-pinned-clientpref-1 vector-feature-night-mode-enabled skin-theme-clientpref-day vector-toc-available";var cookie=document.cookie.match(/(?:^|; )enwikimwclientpreferences=([^;]+)/);if(cookie){cookie[1].split('%2C').forEach(function(pref){className=className.replace(new RegExp('(^| )'+pref.replace(/-clientpref-\w+$|[^\w-]+/g,'')+'-clientpref-\\w+( |$)'),'$1'+pref+'$2');});}document.documentElement.className=className;}());RLCONF={"wgBreakFrames":false,"wgSeparatorTransformTable":["",""],"wgDigitTransformTable":["",""],"wgDefaultDateFormat":"dmy", "wgMonthNames":["","January","February","March","April","May","June","July","August","September","October","November","December"],"wgRequestId":"fe98ec39-2d0d-48d4-a465-adbdd63e29cb","wgCanonicalNamespace":"","wgCanonicalSpecialPageName":false,"wgNamespaceNumber":0,"wgPageName":"IBM_Granite","wgTitle":"IBM Granite","wgCurRevisionId":1261049551,"wgRevisionId":1261049551,"wgArticleId":76093849,"wgIsArticle":true,"wgIsRedirect":false,"wgAction":"view","wgUserName":null,"wgUserGroups":["*"],"wgCategories":["Articles with short description","Short description matches Wikidata","IBM products","IBM software","Large language models","Generative artificial intelligence","Artificial neural networks","2023 software","Free software"],"wgPageViewLanguage":"en","wgPageContentLanguage":"en","wgPageContentModel":"wikitext","wgRelevantPageName":"IBM_Granite","wgRelevantArticleId":76093849,"wgIsProbablyEditable":true,"wgRelevantPageIsProbablyEditable":true,"wgRestrictionEdit":[],"wgRestrictionMove":[], "wgNoticeProject":"wikipedia","wgCiteReferencePreviewsActive":false,"wgFlaggedRevsParams":{"tags":{"status":{"levels":1}}},"wgMediaViewerOnClick":true,"wgMediaViewerEnabledByDefault":true,"wgPopupsFlags":0,"wgVisualEditor":{"pageLanguageCode":"en","pageLanguageDir":"ltr","pageVariantFallbacks":"en"},"wgMFDisplayWikibaseDescriptions":{"search":true,"watchlist":true,"tagline":false,"nearby":true},"wgWMESchemaEditAttemptStepOversample":false,"wgWMEPageLength":7000,"wgRelatedArticlesCompat":[],"wgEditSubmitButtonLabelPublish":true,"wgULSPosition":"interlanguage","wgULSisCompactLinksEnabled":false,"wgVector2022LanguageInHeader":true,"wgULSisLanguageSelectorEmpty":false,"wgWikibaseItemId":"Q124693286","wgCheckUserClientHintsHeadersJsApi":["brands","architecture","bitness","fullVersionList","mobile","model","platform","platformVersion"],"GEHomepageSuggestedEditsEnableTopics":true,"wgGETopicsMatchModeEnabled":false,"wgGEStructuredTaskRejectionReasonTextInputEnabled":false, "wgGELevelingUpEnabledForUser":false};RLSTATE={"ext.globalCssJs.user.styles":"ready","site.styles":"ready","user.styles":"ready","ext.globalCssJs.user":"ready","user":"ready","user.options":"loading","ext.cite.styles":"ready","skins.vector.search.codex.styles":"ready","skins.vector.styles":"ready","skins.vector.icons":"ready","jquery.makeCollapsible.styles":"ready","ext.wikimediamessages.styles":"ready","ext.visualEditor.desktopArticleTarget.noscript":"ready","ext.uls.interlanguage":"ready","wikibase.client.init":"ready","ext.wikimediaBadges":"ready"};RLPAGEMODULES=["ext.cite.ux-enhancements","site","mediawiki.page.ready","jquery.makeCollapsible","mediawiki.toc","skins.vector.js","ext.centralNotice.geoIP","ext.centralNotice.startUp","ext.gadget.ReferenceTooltips","ext.gadget.switcher","ext.urlShortener.toolbar","ext.centralauth.centralautologin","mmv.bootstrap","ext.popups","ext.visualEditor.desktopArticleTarget.init","ext.visualEditor.targetLoader","ext.echo.centralauth", "ext.eventLogging","ext.wikimediaEvents","ext.navigationTiming","ext.uls.interface","ext.cx.eventlogging.campaigns","ext.cx.uls.quick.actions","wikibase.client.vector-2022","ext.checkUser.clientHints","ext.quicksurveys.init","ext.growthExperiments.SuggestedEditSession"]; (RLQ=window.RLQ||[]).push(function(){mw.loader.impl(function(){return["user.options@12s5i",function($,jQuery,require,module){mw.user.tokens.set({"patrolToken":"+\\","watchToken":"+\\","csrfToken":"+\\"}); }];});}); Jump to content

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    1 Foundation models

    ](#Foundation_models)

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    2 See also

    ](#See_also)

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    3 References

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    4 External links

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From Wikipedia, the free encyclopedia

2023 text-generating language model

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| | | | --- | --- |Granite | | | | Developer(s) | IBM Research[1] | | Initial release | November 7, 2023; 12 months ago (2023-11-07) | | Platform | IBM Watsonx (initially)
GitHub
Hugging Face
RHEL AI | | Type | .mw-parser-output .plainlist ol,.mw-parser-output .plainlist ul{line-height:inherit;list-style:none;margin:0;padding:0}.mw-parser-output .plainlist ol li,.mw-parser-output .plainlist ul li{margin-bottom:0}

* Multimodal
* Large language model
* Generative pre-trained transformer
* Foundation model | | License | Proprietary
Code models: Open Source (Apache 2.0)[2] |

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Part of a series on
Machine learning
and data mining
Paradigms

* Supervised learning
* Unsupervised learning
* Semi-supervised learning
* Self-supervised learning
* Reinforcement learning
* Meta-learning
* Online learning
* Batch learning
* Curriculum learning
* Rule-based learning
* Neuro-symbolic AI
* Neuromorphic engineering
* Quantum machine learning
Problems

* Classification
* Generative modeling
* Regression
* Clustering
* Dimensionality reduction
* Density estimation
* Anomaly detection
* Data cleaning
* AutoML
* Association rules
* Semantic analysis
* Structured prediction
* Feature engineering
* Feature learning
* Learning to rank
* Grammar induction
* Ontology learning
* Multimodal learning
Supervised learning
(classification • regression)

* Apprenticeship learning
* Decision trees
* Ensembles
* Bagging
* Boosting
* Random forest
* k-NN
* Linear regression
* Naive Bayes
* Artificial neural networks
* Logistic regression
* Perceptron
* Relevance vector machine (RVM)
* Support vector machine (SVM)
Clustering

* BIRCH
* CURE
* Hierarchical
* k-means
* Fuzzy
* Expectation–maximization (EM)
*
DBSCAN
* OPTICS
* Mean shift
Dimensionality reduction

* Factor analysis
* CCA
* ICA
* LDA
* NMF
* PCA
* PGD
* t-SNE
* SDL
Structured prediction

* Graphical models
* Bayes net
* Conditional random field
* Hidden Markov
Anomaly detection

* RANSAC
* k-NN
* Local outlier factor
* Isolation forest
Artificial neural network

* Autoencoder
* Deep learning
* Feedforward neural network
* Recurrent neural network
* LSTM
* GRU
* ESN
* reservoir computing
* Boltzmann machine
* Restricted
* GAN
* Diffusion model
* SOM
* Convolutional neural network
* U-Net
* LeNet
* AlexNet
* DeepDream
* Neural radiance field
* Transformer
* Vision
* Mamba
* Spiking neural network
* Memtransistor
* Electrochemical RAM (ECRAM)
Reinforcement learning

* Q-learning
* SARSA
* Temporal difference (TD)
* Multi-agent
* Self-play
Learning with humans

* Active learning
* Crowdsourcing
* Human-in-the-loop
* RLHF
Model diagnostics

* Coefficient of determination
* Confusion matrix
* Learning curve
* ROC curve
Mathematical foundations

* Kernel machines
* Bias–variance tradeoff
* Computational learning theory
* Empirical risk minimization
* Occam learning
* PAC learning
* Statistical learning
* VC theory
Journals and conferences

* ECML PKDD
* NeurIPS
* ICML
* ICLR
* IJCAI
* ML
* JMLR
Related articles

* Glossary of artificial intelligence
* List of datasets for machine-learning research
* List of datasets in computer vision and image processing
* Outline of machine learning
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* v
* t
* e

IBM Granite is a series of decoder-only AI foundation models created by IBM. It was announced on September 7, 2023,[3][4] and an initial paper was published 4 days later.[5] Initially intended for use in the IBM's cloud-based data and generative AI platform Watsonx along with other models,[6] IBM opened the source code of some code models.[7] Granite models are trained on datasets curated from Internet, academic publishings, code datasets, legal and finance documents.[8][9][1]

Foundation models

[edit]

A foundation model is an AI model trained on broad data at scale such that it can be adapted to a wide range of downstream tasks.[10]

Granite's first foundation models were Granite.13b.instruct and Granite.13b.chat. The "13b" in their name comes from 13 billion, the amount of parameters they have as models, lesser than most of the larger models of the time. Later models vary from 3 to 34 billion parameters.[3][11]

On May 6, 2024, IBM released the source code of four variations of Granite Code Models under Apache 2, an open source permissive license that allows completely free use, modification and sharing of the software, and put them on Hugging Face for public use.[12][13] According to IBM's own report, Granite 8b outperforms Llama 3 on several coding related tasks within similar range of parameters.[14][15]

See also

[edit]

References

[edit]

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  1. ^ a b .mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}McDowell, Steve. "IBM's New Granite Foundation Models Enable Safe Enterprise AI". Forbes.
  2. ^ ibm-granite/granite-code-models, IBM Granite, 2024-05-08, retrieved 2024-05-08
  3. ^ a b Nirmal, Dinesh (September 7, 2023). "Building AI for business: IBM's Granite foundation models". IBM.
  4. ^ "IBM debuts Granite series of hardware-efficient language models". September 7, 2023.
  5. ^ "Granite Foundation Models" (PDF). IBM. 2023-11-30.
  6. ^ Fritts, Harold (2024-04-22). "IBM Adds Meta Llama 3 To watsonx, Expands AI Offerings". StorageReview.com. Retrieved 2024-05-08.
  7. ^ Jindal, Siddharth (2024-05-07). "IBM Releases Open-Source Granite Code Models, Outperforms Llama 3". Analytics India Magazine. Retrieved 2024-05-08.
  8. ^ Azhar, Ali (2024-04-08). "IBM Patents a Faster Method to Train LLMs for Enterprises". Datanami. Retrieved 2024-05-08.
  9. ^ Wiggers, Kyle (2023-09-07). "IBM rolls out new generative AI features and models". TechCrunch. Retrieved 2024-05-08.
  10. ^ "Introducing the Center for Research on Foundation Models (CRFM)". Stanford HAI. 18 August 2021.
  11. ^ Pawar, Sahil (2023-09-11). "IBM Introduces Granite Series LLM Models for Watsonx Platform". Analytics Drift. Retrieved 2024-05-09.
  12. ^ Nine, Adrianna (May 7, 2024). "IBM Makes Granite AI Models Open-Source Under New InstructLab Platform". ExtremeTech.
  13. ^ "IBM open-sources its Granite AI models - and they mean business". ZDNET. Retrieved 2024-05-21.
  14. ^ Jindal, Siddharth (2024-05-07). "IBM Releases Open-Source Granite Code Models, Outperforms Llama 3". Analytics India Magazine. Retrieved 2024-05-09.
  15. ^ Synced (2024-05-13). "IBM's Granite Code: Powering Enterprise Software Development with AI Precision | Synced". syncedreview.com. Retrieved 2024-05-21.

External links

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IBM

History

Products

Hardware
Current * Mainframe
* IBM Z
* Power microprocessors
* Power Systems
* Storage
* FlashSystem
* DS8000
* Quantum
* Q System One
* Q System Two
* Eagle
* Osprey
* Heron
* Condor
Former * Blue Gene
* Cell microprocessors
* PowerPC
* Midrange computer
* Personal Computer
* Selectric
* ThinkPad

Other

Business
entities
Current * Apptio
* Center for The Business of Government
* Consulting
* Promontory
* Kenexa
* International subsidiaries
* India
* Press
* Red Hat
* Research
Former * AdStar
* AIM alliance
* Kaleida Labs
* Taligent
* Ambra Computer
* Cognos
* EduQuest
* Kyndryl
* Lexmark
* Merative
* Microelectronics
* Product Center
* Science Research Associates
* Service Bureau
* The Weather Company (Weather Underground)

Facilities

Initiatives

Inventions

Terminology

CEOs

Board of
directors

Other

Artificial intelligence

Concepts

Applications

Implementations
Audio–visual * AlexNet
* WaveNet
* Human image synthesis
* HWR
* OCR
* Speech synthesis
* ElevenLabs
* Speech recognition
* Whisper
* Facial recognition
* AlphaFold
* Text-to-image models
* DALL-E
* Flux
* Ideogram
* Midjourney
* Stable Diffusion
* Text-to-video models
* Sora
* Dream Machine
* VideoPoet
* Music generation
* Suno AI
* Udio
Text * Word2vec
* Seq2seq
* GloVe
* BERT
* T5
* Llama
* Chinchilla AI
* PaLM
* GPT
* 1
* 2
* 3
* J
* ChatGPT
* 4
* 4o
* o1
* Claude
* Gemini
* chatbot
* Grok
* LaMDA
* BLOOM
* Project Debater
* IBM Watson
* IBM Watsonx
* Granite
* PanGu-Σ
Decisional * AlphaGo
* AlphaZero
* OpenAI Five
* Self-driving car
* MuZero
* Action selection
* AutoGPT
* Robot control

People

Architectures

Retrieved from "https://en.wikipedia.org/w/index.php?title=IBM_Granite&oldid=1261049551"

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