# FastText > Mediated Wiki article. Canonical URL: https://mediated.wiki/source/FastText > Markdown URL: https://mediated.wiki/source/FastText.md > Source: https://en.wikipedia.org/wiki/FastText > Source revision: 1349191325 > License: Creative Commons Attribution-ShareAlike 4.0 International (https://creativecommons.org/licenses/by-sa/4.0/) Programming library This article is about the text classification library. For the teletext feature, see [Fastext](/source/Fastext). fastText Developer Facebook's AI Research (FAIR) lab[1] Release November 9, 2015; 10 years ago (2015-11-09) Stable release 0.9.2[2] / April 28, 2020; 6 years ago (2020-04-28) Written in C++, Python Platform Linux, macOS, Windows Type Machine learning library License MIT License Website fasttext.cc Repository github.com/facebookresearch/fastText **fastText** is a library for learning of [word embeddings](/source/Word_embedding) and text classification created by [Facebook](/source/Facebook)'s AI Research (FAIR) lab.[3][4][5][6] The model allows one to create an [unsupervised learning](/source/Unsupervised_learning) or [supervised learning](/source/Supervised_learning) algorithm for obtaining vector representations for words. Facebook makes available pretrained models for 294 languages.[7][8] Several papers describe the techniques used by fastText.[9][10][11][12] The GitHub repository was archived on March 19, 2024. ## See also - [Word2vec](/source/Word2vec) - [GloVe](/source/GloVe) - [Neural network (machine learning)](/source/Neural_network_(machine_learning)) - [Natural language processing](/source/Natural_language_processing) - [Comparison of machine learning software](/source/Comparison_of_machine_learning_software) ## References 1. **[^](#cite_ref-1)** Mannes, John. ["Facebook's fastText library is now optimized for mobile"](https://techcrunch.com/2017/05/02/facebooks-fasttext-library-is-now-optimized-for-mobile/). *[TechCrunch](/source/TechCrunch)*. Retrieved 12 January 2018. 1. **[^](#cite_ref-gith_face_v0.9.2_2-0)** Onur Çelebi (2020-04-28). ["facebookresearch/fastText/releases/tag/v0.9.2"](https://github.com/facebookresearch/fastText/releases/tag/v0.9.2). *Facebook*. Retrieved 2020-11-21. 1. **[^](#cite_ref-3)** Mannes, John. ["Facebook's fastText library is now optimized for mobile"](https://techcrunch.com/2017/05/02/facebooks-fasttext-library-is-now-optimized-for-mobile/). *[TechCrunch](/source/TechCrunch)*. Retrieved 12 January 2018. 1. **[^](#cite_ref-4)** Ryan, Kevin J. ["Facebook's New Open Source Software Can Learn 1 Billion Words in 10 Minutes"](https://www.inc.com/kevin-j-ryan/facebook-open-source-fasttext-learns-1-billion-words-in-10-minutes.html). *[Inc.](/source/Inc._(magazine))* Retrieved 12 January 2018. 1. **[^](#cite_ref-5)** Low, Cherlynn. ["Facebook is open-sourcing its AI bot-building research"](https://www.engadget.com/2016/08/18/facebook-open-sourcing-fasttext/). *[Engadget](/source/Engadget)*. Retrieved 12 January 2018. 1. **[^](#cite_ref-6)** Mannes, John. ["Facebook's Artificial Intelligence Research lab releases open source fastText on GitHub"](https://techcrunch.com/2016/08/18/facebooks-artificial-intelligence-research-lab-releases-open-source-fasttext-on-github/). *[TechCrunch](/source/TechCrunch)*. Retrieved 12 January 2018. 1. **[^](#cite_ref-7)** Sabin, Dyani. ["Facebook Makes A.I. Program Available in 294 Languages"](https://www.inverse.com/article/31075-facebook-machine-learning-language-fasttext). *[Inverse](/source/Inverse_(website))*. Retrieved 12 January 2018. 1. **[^](#cite_ref-8)** ["Wiki word vectors"](https://fasttext.cc/docs/en/pretrained-vectors.html). *fastText*. Retrieved 26 November 2020. 1. **[^](#cite_ref-9)** ["References · fastText"](https://fasttext.cc/index.html). *fasttext.cc*. Retrieved 2021-09-08. 1. **[^](#cite_ref-10)** Bojanowski, Piotr; Grave, Edouard; Joulin, Armand; Mikolov, Tomas (2017-06-19). "Enriching Word Vectors with Subword Information". [arXiv](/source/ArXiv_(identifier)):[1607.04606](https://arxiv.org/abs/1607.04606) [[cs.CL](https://arxiv.org/archive/cs.CL)]. 1. **[^](#cite_ref-11)** Joulin, Armand; Grave, Edouard; Bojanowski, Piotr; Mikolov, Tomas (2016-08-09). "Bag of Tricks for Efficient Text Classification". [arXiv](/source/ArXiv_(identifier)):[1607.01759](https://arxiv.org/abs/1607.01759) [[cs.CL](https://arxiv.org/archive/cs.CL)]. 1. **[^](#cite_ref-12)** Joulin, Armand; Grave, Edouard; Bojanowski, Piotr; Douze, Matthijs; Jégou, Hérve; Mikolov, Tomas (2016-12-12). "FastText.zip: Compressing text classification models". [arXiv](/source/ArXiv_(identifier)):[1612.03651](https://arxiv.org/abs/1612.03651) [[cs.CL](https://arxiv.org/archive/cs.CL)]. ## External links - [fastText](https://fasttext.cc) - [https://research.fb.com/downloads/fasttext/](https://research.fb.com/downloads/fasttext/) v t e Natural language processing General terms AI-complete Bag-of-words n-gram Bigram Trigram Computational linguistics Natural language understanding Stop words Text processing Text analysis Argument mining Collocation extraction Concept mining Coreference resolution Deep linguistic processing Distant reading Information extraction Named-entity recognition Ontology learning Parsing semantic syntactic Part-of-speech tagging Semantic analysis Semantic role labeling Semantic decomposition Semantic similarity Sentiment analysis Stylometry adversarial Terminology extraction Text mining Textual entailment Truecasing Word-sense disambiguation Word-sense induction Text segmentation Compound-term processing Lemmatization Lexical analysis Text chunking Stemming Sentence segmentation Word segmentation Automatic summarization Multi-document summarization Sentence extraction Text simplification Machine translation Computer-assisted Example-based Rule-based Statistical Transfer-based Neural Distributional semantics models BERT Document-term matrix Explicit semantic analysis fastText GloVe Language model large small Latent semantic analysis Long short-term memory Seq2seq Transformer Word embedding Word2vec Language resources, datasets and corpora Types and standards Corpus linguistics Lexical resource Linguistic Linked Open Data Machine-readable dictionary Parallel text PropBank Semantic network Simple Knowledge Organization System Speech corpus Text corpus Thesaurus (information retrieval) Treebank Universal Dependencies Data BabelNet Bank of English DBpedia FrameNet Google Ngram Viewer UBY WordNet Wikidata Automatic identification and data capture Speech recognition Speech segmentation Speech synthesis Natural language generation Topic model Document classification Dynamic topic model Latent Dirichlet allocation Pachinko allocation Computer-assisted reviewing Automated essay scoring Concordancer Grammar checker Predictive text Pronunciation assessment Spell checker Natural language user interface Chatbot Interactive fiction Prompt engineering Question answering Virtual assistant Voice user interface Visual-linguistic Automatic image annotation CLIP Multimodal sentiment analysis Optical character recognition Vision-language model Vision–language–action model Related Formal semantics Gensim Hallucination Natural Language Toolkit spaCy This free and open-source software article is a stub. You can help Wikipedia by adding missing information. - [v](https://en.wikipedia.org/wiki/Template:Free-software-stub) - [t](/source/Template_talk%3AFree-software-stub) - [e](https://en.wikipedia.org/wiki/Special:EditPage/Template:Free-software-stub) --- Adapted from the Wikipedia article [FastText](https://en.wikipedia.org/wiki/FastText) by Wikipedia contributors ([contributor history](https://en.wikipedia.org/wiki/FastText?action=history)). Available under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). Changes may have been made.