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An implementation of the GloVe model for learning word representations is provided, and describe how to download web-dataset vectors or train your own. See the `project page <http://nlp.stanford.edu/projects/glove/>`__ or the `paper <http://nlp.stanford.edu/pubs/glove.pdf>`__ for more information on glove vectors.
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contextualized word representations
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FastText
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fastText is a library for efficient learning of word representations and sentence classification.
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**Github:** `facebookresearch/fastText <https://github.com/facebookresearch/fastText>`__
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**Models**
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- Recent state-of-the-art `English word vectors <https://fasttext.cc/docs/en/english-vectors.html>`__.
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- Word vectors for `157 languages trained on Wikipedia and Crawl <https://github.com/facebookresearch/fastText/blob/master/docs/crawl-vectors.md>`__.
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- Models for `language identification <https://fasttext.cc/docs/en/language-identification.html#content>`__ and `various supervised tasks <https://fasttext.cc/docs/en/supervised-models.html#content>`__.
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**Supplementary data :**
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- The preprocessed `YFCC100M data <https://fasttext.cc/docs/en/dataset.html#content>`__ .
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**FAQ**
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You can find `answers to frequently asked questions <https://fasttext.cc/docs/en/faqs.html#content>`__ on Their project `website <https://fasttext.cc/>`__.
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**Cheatsheet**
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Also a `cheatsheet <https://fasttext.cc/docs/en/cheatsheet.html#content>`__ is provided full of useful one-liners.
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~~~~~~~~~~~~~~
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Weighted Words

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