Embeds text documents using sent2vec
Project description
Sentence Embedding
A python wrapper for embedding short texts or sentences using sent2vec, which draws on FastText.
To embed a list of strings documents, use:
from nk_sent2vec import Sent2Vec
vectorizer = Sent2Vec(path = '/root/models/torontobooks_unigrams.bin')
print(vectorizer.embed_sentences(sentences=documents))
Testing
Tests can be run using pytest -s tests
Also see makefile for default commands
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