Magnitude: A Fast, Efficient Universal Vector Embedding Utility Package
October 26, 2018 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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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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