Transformers: State-of-the-Art Natural Language Processing
Transformers: современное состояние обработки естественного языка
2020-01-01
SCID: 54.1/grws3e4v
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Hugging Face TransformersNatural Language ProcessingPretrained Transformer modelsSystem Demonstrations EMNLP 2020Transformers
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Abstract (AI)
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, Alexander Rush. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. 2020.
Key Findings
1
The Transformers library provides a state-of-the-art toolkit for natural language processing tasks.
2
The contribution is collaborative and large-scale, authored by many contributors, suggesting broad community involvement and maintenance.
3
The work is presented as a system demonstration at EMNLP 2020, indicating practical, usable software contributions.
Research Object
Transformers library and toolkit for state-of-the-art natural language processing
Research Subject
Capabilities, features, and practical application of the Transformers framework for enabling state-of-the-art NLP models and demonstrations
Publication Details
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2020-01-01
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References available in scid.ai6
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