Magnitude: A Fast, Efficient Universal Vector Embedding Utility Package

October 26, 2018 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Ajay Patel, Alexander Sands, Chris Callison-Burch, Marianna Apidianaki arXiv ID 1810.11190 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 34 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 4 months ago
Abstract
Vector space embedding models like word2vec, GloVe, fastText, and ELMo 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.
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