Metadata-Version: 2.1
Name: nk-sent2vec
Version: 1.4.2
Summary: Embeds text documents using sent2vec
Home-page: UNKNOWN
Author: New Knowledge
License: BSD-3-Clause
Description: # Sentence Embedding
        A python wrapper for embedding short texts or sentences using [sent2vec](https://github.com/epfml/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
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
