← 返回资源分享
HuggingFace's Transformers: State-of-the-art Natural Language Processing
论文
论文
发布时间2019-10-09
发表arXiv:1910.03771
作者:Thomas Wolf,Julien Chaumond,Clement Delangue,Alexander M. Rush,Yacine Jernite,Victor Sanh,Patrick von Platen,Joe Davison,Sylvain Gugger,Lysandre Debut,Sam Shleifer,Canwen Xu,Quentin Lhoest,Teven Le Scao,Mariama Drame,Julien Plu,Pierric Cistac,Rémi Louf,Anthony Moi,Tim Rault,Morgan Funtowicz,Clara Ma
详细介绍
Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to effectively utilize this capacity for a wide variety of tasks. \textit{Transformers} is an open-source library with the goal of opening up these advances to the wider machine learning community. The library consists of carefully engineered state-of-the art Transformer architectures under a unified API. Backing this library is a curated collection of pretrained models made by and available for the community. \textit{Transformers} is designed to be extensible by researchers, simple for practitioners, and fast and robust in industrial deployments. The library is available at \url{https://github.com/huggingface/transformers}.
代码仓库 (9)
huggingface/transformersPyTorch
devhemza/BERTweet_sentiment_analysisPyTorch
amoramine/Pegasus_with_Longformer_summarizationPyTorch
amoramine/Pegasus_Longformer_summarizationPyTorch
ufal/wembedding_serviceTensorFlow
princeton-nlp/mabelPyTorch
ncfrey/litmatterPyTorch
Mind23-2/MindCode-154MindSpore
phaelishall/semeval2020-codePyTorch
