A feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity. It is primarily intended to be a simpler / faster alternative to Gensim but can be used as a generic key-vector store for domains outside NLP. It offers unique features like out-of-vocabulary lookups and streaming of large models over HTTP. Published in our paper at EMNLP 2018 and available on arXiv.

Features

  • A fast, simple vector embedding utility library
  • Documentation available
  • Examples available
  • Basic Out-of-Vocabulary Keys
  • Pre-converted Magnitude Formats of Popular Embeddings Models
  • Additional Featurization (Parts of Speech, etc.)

Project Samples

Project Activity

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Categories

Machine Learning

License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software

Registered

2024-08-16