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To get vector of a word, I can use:
model["word"]
but if I want to get the vector of a sentence, I need to either sum vectors of all words or get average of all vectors.
Does FastText provide a method to do this?
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fastText is another word embedding method that is an extension of the word2vec model. Instead of learning vectors for words directly, fastText represents each word as an n-gram of characters.
The biggest benefit of using FastText is that it generate better word embeddings for rare words, or even words not seen during training because the n-gram character vectors are shared with other words. This is something that Word2Vec and GLOVE cannot achieve.
FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware.
FastText is an open-source, free library from Facebook AI Research(FAIR) for learning word embeddings and word classifications. This model allows creating unsupervised learning or supervised learning algorithm for obtaining vector representations for words.
If you want to compute vector representations of sentences or paragraphs, please use:
$ ./fasttext print-sentence-vectors model.bin < text.txt
This assumes that the text.txt file contains the paragraphs that you want to get vectors for. The program will output one vector representation per line in the file.
This has been clearly mentioned in the README of fasttext repo. https://github.com/facebookresearch/fastText
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