fastText
 | |
| Developer(s) | Facebook's AI Research (FAIR) lab[1] |
|---|---|
| Initial release | November 9, 2015 |
| Stable release | 0.9.2[2]
/ April 28, 2020 |
| Repository | github |
| Written in | C++, Python |
| Platform | Linux, macOS, Windows |
| Type | Machine learning library |
| License | MIT License |
| Website | fasttext |
fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab.[3][4][5][6] The model allows one to create an unsupervised learning or 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]
See also
[edit]References
[edit]- ^ Mannes, John. "Facebook's fastText library is now optimized for mobile". TechCrunch. Retrieved 12 January 2018.
- ^ Onur Çelebi (2020-04-28). "facebookresearch/fastText/releases/tag/v0.9.2". Facebook. Retrieved 2020-11-21.
- ^ Mannes, John. "Facebook's fastText library is now optimized for mobile". TechCrunch. Retrieved 12 January 2018.
- ^ Ryan, Kevin J. "Facebook's New Open Source Software Can Learn 1 Billion Words in 10 Minutes". Inc. Retrieved 12 January 2018.
- ^ Low, Cherlynn. "Facebook is open-sourcing its AI bot-building research". Engadget. Retrieved 12 January 2018.
- ^ Mannes, John. "Facebook's Artificial Intelligence Research lab releases open source fastText on GitHub". TechCrunch. Retrieved 12 January 2018.
- ^ Sabin, Dyani. "Facebook Makes A.I. Program Available in 294 Languages". Inverse. Retrieved 12 January 2018.
- ^ "Wiki word vectors". fastText. Retrieved 26 November 2020.
- ^ "References · fastText". fasttext.cc. Retrieved 2021-09-08.
- ^ Bojanowski, Piotr; Grave, Edouard; Joulin, Armand; Mikolov, Tomas (2017-06-19). "Enriching Word Vectors with Subword Information". arXiv:1607.04606 [cs.CL].
- ^ Joulin, Armand; Grave, Edouard; Bojanowski, Piotr; Mikolov, Tomas (2016-08-09). "Bag of Tricks for Efficient Text Classification". arXiv:1607.01759 [cs.CL].
- ^ Joulin, Armand; Grave, Edouard; Bojanowski, Piotr; Douze, Matthijs; Jégou, Hérve; Mikolov, Tomas (2016-12-12). "FastText.zip: Compressing text classification models". arXiv:1612.03651 [cs.CL].
External links
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