Provides a set of tools for downloading and applying the fasttext word embeddings. All embeddings are fit in-memory for speed. The resulting embeddings can be used for supervised and unsupervised learning over a text-based corpus. Embeddings are consistent across languages, so similar words in different language should get mapped to similar vectors in the output space.
|Maintainer||Taylor B. Arnold <email@example.com>|
|Package repository||View on GitHub|
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