| Facebook's FAST TEXT |
| FastText - library for efficient text classification and representation learning.
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| Hierarchical-Neural-Autoencoder - Implementations of the three models presented in the paper "A Hierarchical Neural Autoencoder for Paragraphs and Documents" by Jiwei Li, Minh-Thang Luong and Dan Jurafsky, ACL 2015
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| Implementation of a deep recursive net over binary parse trees (code for NIPS2014 paper) Ozan Irsoy |
| item2vec: Tensorflow implementation |
| Python implementation of Word Movers Distance (WMD) |
| SERT - semantic retrieval toolkit
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| Skip-thought vectors Ryan Kiros |
| Starspace - Learning embeddings for classification, retrieval and ranking.
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| TensorFlow implementation of skip-thought model |
| text2vec an R package which provides an efficient framework with a concise API for text analysis and natural language processing (NLP). - an R package which provides an efficient framework with a concise API for text analysis and natural language processing (NLP).
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| Tweet2Vec - Learning tweet embeddings using character-level CNN-LSTM encoder-decoder.
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| Tweet2Vec - Character-Based Distributed Representations for Social Media.
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| wang2vec Extension of the original word2vec using different architectures |
| Word Mover's Distance (WMD) Matthew J Kusner |
| word2vec - This is an original word2vec on GitHub (maitained by Dav Yaginuma et al)
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| word2vecf - a modification of Mikolov's word2vec, which, among other things, can learn embeddings for arbitrary contexts.
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