FAIR open-sources fastText

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FAIR open-sourced fastText, a library for efficient text classification and learning word vector representations. FastText employs hierarchical classifiers with Huffman coding for speed, and uses bag of n-grams and subword information to improve accuracy. It achieves state-of-the-art performance on standard problems like sentiment analysis and tag prediction, often matching deep learning models in accuracy but being significantly faster for training and evaluation. It also supports learning word vector representations, outperforming word2vec and other methods, especially for morphologically rich languages.