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
1 maintainer
Metadata
1 maintainer
Release files for nk-sent2vec 1.4.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| nk_sent2vec-1.4.2.tar.gz | 3.3 kB | Without provenance | Details for nk_sent2vec-1.4.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| nk_sent2vec-1.4.2-py3-none-any.whl | Python 3 | none | any | Details for nk_sent2vec-1.4.2-py3-none-any.whl |
Total release size: 7.4 kB
Release files / nk_sent2vec-1.4.2.tar.gz
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| Size | 3.3 kB |
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Release files / nk_sent2vec-1.4.2-py3-none-any.whl
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| Size | 4.1 kB |
| Tags | Python 3 |
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