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2019 NAACL NAACL 2019

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

Abstract

Abstractfairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks. The toolkit is based on PyTorch and supports distributed training across multiple GPUs and machines. We also support fast mixed-precision training and inference on modern GPUs. A demo video can be found at https://www.youtube.com/watch?v=OtgDdWtHvto

🌉 Interdisciplinary Bridge — Computer Science and Natural Language Processing
🧭 Keyword Pioneer — neural toolkit
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning

Authors

Myle Ott , Sergey Edunov , Alexei Baevski , Angela Fan , Sam Gross , Nathan Ng , David Grangier , Michael Auli

Topics

Deep Learning > Architectures > Transformers Natural Language Processing > Generation > Language Modeling Natural Language Processing > Resources & Methods > Text Representation Computer Science > Applications > Software Engineering

Keywords

sequence modeling neural machine translation text generation neural toolkit software framework distributed training language model
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