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A Light-weight Python NLP Library

Project description


A Light-weight and Fast Python NLP Library

The plan is to provide light-weight neural models for various downstream NLP tasks such as POS Taggging, Named Entity Recognition, Sentiment Analysis, etc. However, right now POS Tagging is the only task that is supported.



pip install convex

From Source

git clone
cd convex
pip install -e .


The model only needs to be downloaded the first time the tagger is used or after the package is updated

import convex # Download all the necessary models
tagger = convex.PosTagger() # Initialize the Pos Tagging Pipeline
tagger("Let's see how this new tagger works.") # Tag a sentence

Output -

[('Let', 'VERB'), ("'s", 'PRON'), ('see', 'VERB'), ('how', 'ADV'), ('well', 'ADV'), ('this', 'DET'), ('new', 'ADJ'), ('tagger', 'NOUN'), ('works', 'NOUN')]

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