Transformers: State-of-the-Art Natural Language Processing

Thomas Wolf; Lysandre Debut; Victor Sanh; Julien Chaumond; Clément Delangue; Anthony Moi; Pierric Cistac; Tim Rault; Rémi 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 M. Rush

doi:10.18653/v1/2020.emnlp-demos.6

Key Points

To introduce an open-source library that unifies state-of-the-art transformer architectures under an accessible, extensible, and framework-interoperable interface.
Designed a unified API supporting state-of-the-art transformer architectures across PyTorch and TensorFlow deep learning frameworks.
Integrated model hub repositories to facilitate direct access to pretrained weights, tokenizers, and task-specific fine-tuning pipelines.
Optimized compute workflows for research experimentation, distributed training, and production inference.
Standardized access to dozens of state-of-the-art architectures for text classification, generation, summarization, and translation.
Eliminated boilerplate implementation barriers across diverse natural language processing pipelines and deep learning backends.

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Implication

System demonstration presents a unified open-source library for natural language processing, streamlining transformer model deployment across diverse computing frameworks.

Abstract

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.

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Wolf et al. (2020) studied this question.

synapsesocial.com/papers/6960178b942be801b55caa36 https://doi.org/10.18653/v1/2020.emnlp-demos.6

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Transformers: State-of-the-Art Natural Language Processing

Key Points

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Implication

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Transformers: State-of-the-Art Natural Language Processing

Key Points

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