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README.md
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README.md
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<p align="center">
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<a href="https://github.com/huggingface/transformers/blob/master/LICENSE">
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<a href="https://github.com/huggingface/transformers/blob/master/LICENSE">
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<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformer?style=flat-square">
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<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/master">
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<a href="https://github.com/huggingface/transformers/blob/master/LICENSE">
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<a href="https://github.com/huggingface/transformers/blob/master/LICENSE">
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<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue&style=flat-square">
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<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
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</a>
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<a href="https://huggingface.co/transformers/index.html">
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<a href="https://huggingface.co/transformers/index.html">
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<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/transformers/index.html.svg?down_color=red&down_message=offline&style=flat-square&up_message=online">
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<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/transformers/index.html.svg?down_color=red&down_message=offline&up_message=online">
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<a href="https://github.com/huggingface/transformers/releases">
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<a href="https://github.com/huggingface/transformers/releases">
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<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg?style=flat-square">
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<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
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State-of-the-art Natural Language Processing (NLP) for TensorFlow 2.0 and PyTorch.
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<h3 align="center">
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<p>State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch
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</h3>
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🤗 Transformers (formerly known as `pytorch-transformers` and `pytorch-pretrained-bert`) provides general-purpose architectures (BERT, GPT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with more than 32+ pretrained checkpoints in 100+ languages.
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🤗 Transformers (formerly known as `pytorch-transformers` and `pytorch-pretrained-bert`) provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
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### Features
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Features
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- As easy to use as pytorch-transformers
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- As easy to use as pytorch-transformers
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- As powerful and concise as Keras
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- As powerful and concise as Keras
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- High performance on NLU and NLG tasks
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- High performance on NLU and NLG tasks
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