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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

Release files for nk-sent2vec 1.4.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for nk-sent2vec 1.4.2
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Table of built distributions (wheels) for nk-sent2vec 1.4.2
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nk_sent2vec-1.4.2-py3-none-any.whl Python 3 none any Details

Total release size: 7.4 kB

Release files / nk_sent2vec-1.4.2.tar.gz

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Release files / nk_sent2vec-1.4.2-py3-none-any.whl

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