Sam Gross

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2019

pdf bib
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Myle Ott | Sergey Edunov | Alexei Baevski | Angela Fan | Sam Gross | Nathan Ng | David Grangier | Michael Auli
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)

fairseq 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
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