Alexander Sands


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Magnitude: A Fast, Efficient Universal Vector Embedding Utility Package
Ajay Patel | Alexander Sands | Chris Callison-Burch | Marianna Apidianaki
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Vector space embedding models like word2vec, GloVe, and fastText are extremely popular representations in natural language processing (NLP) applications. We present Magnitude, a fast, lightweight tool for utilizing and processing embeddings. Magnitude is an open source Python package with a compact vector storage file format that allows for efficient manipulation of huge numbers of embeddings. Magnitude performs common operations up to 60 to 6,000 times faster than Gensim. Magnitude introduces several novel features for improved robustness like out-of-vocabulary lookups.