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committedSep 27, 2021
Release: v4.11.0
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‎README.md

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1. **[EncoderDecoder](https://huggingface.co/transformers/model_doc/encoderdecoder.html)** (from Google Research) released with the paper [Leveraging Pre-trained Checkpoints for Sequence Generation Tasks](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn.
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1. **[ELECTRA](https://huggingface.co/transformers/model_doc/electra.html)** (from Google Research/Stanford University) released with the paper [ELECTRA: Pre-training text encoders as discriminators rather than generators](https://arxiv.org/abs/2003.10555) by Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning.
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1. **[FlauBERT](https://huggingface.co/transformers/model_doc/flaubert.html)** (from CNRS) released with the paper [FlauBERT: Unsupervised Language Model Pre-training for French](https://arxiv.org/abs/1912.05372) by Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoît Crabbé, Laurent Besacier, Didier Schwab.
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1. **[FNet](https://huggingface.co/transformers/master/model_doc/fnet.html)** (from Google Research) released with the paper [FNet: Mixing Tokens with Fourier Transforms](https://arxiv.org/abs/2105.03824) by James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, Santiago Ontanon.
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1. **[FNet](https://huggingface.co/transformers/model_doc/fnet.html)** (from Google Research) released with the paper [FNet: Mixing Tokens with Fourier Transforms](https://arxiv.org/abs/2105.03824) by James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, Santiago Ontanon.
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1. **[Funnel Transformer](https://huggingface.co/transformers/model_doc/funnel.html)** (from CMU/Google Brain) released with the paper [Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing](https://arxiv.org/abs/2006.03236) by Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le.
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1. **[GPT](https://huggingface.co/transformers/model_doc/gpt.html)** (from OpenAI) released with the paper [Improving Language Understanding by Generative Pre-Training](https://blog.openai.com/language-unsupervised/) by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.
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1. **[GPT-2](https://huggingface.co/transformers/model_doc/gpt2.html)** (from OpenAI) released with the paper [Language Models are Unsupervised Multitask Learners](https://blog.openai.com/better-language-models/) by Alec Radford*, Jeffrey Wu*, Rewon Child, David Luan, Dario Amodei** and Ilya Sutskever**.
@@ -267,9 +267,9 @@ Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.
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1. **[RemBERT](https://huggingface.co/transformers/model_doc/rembert.html)** (from Google Research) released with the paper [Rethinking embedding coupling in pre-trained language models](https://arxiv.org/pdf/2010.12821.pdf) by Hyung Won Chung, Thibault Févry, Henry Tsai, M. Johnson, Sebastian Ruder.
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1. **[RoBERTa](https://huggingface.co/transformers/model_doc/roberta.html)** (from Facebook), released together with the paper a [Robustly Optimized BERT Pretraining Approach](https://arxiv.org/abs/1907.11692) by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov.
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1. **[RoFormer](https://huggingface.co/transformers/model_doc/roformer.html)** (from ZhuiyiTechnology), released together with the paper a [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://arxiv.org/pdf/2104.09864v1.pdf) by Jianlin Su and Yu Lu and Shengfeng Pan and Bo Wen and Yunfeng Liu.
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1. **[SpeechEncoderDecoder](https://huggingface.co/transformers/master/model_doc/speechencoderdecoder.html)**
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1. **[SpeechEncoderDecoder](https://huggingface.co/transformers/model_doc/speechencoderdecoder.html)**
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1. **[SpeechToTextTransformer](https://huggingface.co/transformers/model_doc/speech_to_text.html)** (from Facebook), released together with the paper [fairseq S2T: Fast Speech-to-Text Modeling with fairseq](https://arxiv.org/abs/2010.05171) by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Dmytro Okhonko, Juan Pino.
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1. **[SpeechToTextTransformer2](https://huggingface.co/transformers/master/model_doc/speech_to_text_2.html)** (from Facebook), released together with the paper [Large-Scale Self- and Semi-Supervised Learning for Speech Translation](https://arxiv.org/abs/2104.06678) by Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis Conneau.
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1. **[SpeechToTextTransformer2](https://huggingface.co/transformers/model_doc/speech_to_text_2.html)** (from Facebook), released together with the paper [Large-Scale Self- and Semi-Supervised Learning for Speech Translation](https://arxiv.org/abs/2104.06678) by Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis Conneau.
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1. **[Splinter](https://huggingface.co/transformers/model_doc/splinter.html)** (from Tel Aviv University), released together with the paper [Few-Shot Question Answering by Pretraining Span Selection](https://arxiv.org/abs/2101.00438) by Ori Ram, Yuval Kirstain, Jonathan Berant, Amir Globerson, Omer Levy.
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1. **[SqueezeBert](https://huggingface.co/transformers/model_doc/squeezebert.html)** (from Berkeley) released with the paper [SqueezeBERT: What can computer vision teach NLP about efficient neural networks?](https://arxiv.org/abs/2006.11316) by Forrest N. Iandola, Albert E. Shaw, Ravi Krishna, and Kurt W. Keutzer.
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1. **[T5](https://huggingface.co/transformers/model_doc/t5.html)** (from Google AI) released with the paper [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://arxiv.org/abs/1910.10683) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.

‎docs/source/conf.py

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# The short X.Y version
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version = ""
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# The full version, including alpha/beta/rc tags
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release = "4.11.0.dev0"
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release = "4.11.0"
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‎docs/source/index.rst

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28. :doc:`FlauBERT <model_doc/flaubert>` (from CNRS) released with the paper `FlauBERT: Unsupervised Language Model
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Pre-training for French <https://arxiv.org/abs/1912.05372>`__ by Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne,
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Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoît Crabbé, Laurent Besacier, Didier Schwab.
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29. `FNet <https://huggingface.co/transformers/master/model_doc/fnet.html>`__ (from Google Research) released with the
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paper `FNet: Mixing Tokens with Fourier Transforms <https://arxiv.org/abs/2105.03824>`__ by James Lee-Thorp, Joshua
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Ainslie, Ilya Eckstein, Santiago Ontanon.
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29. :doc:`FNet <model_doc/fnet>` (from Google Research) released with the paper `FNet: Mixing Tokens with Fourier
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Transforms <https://arxiv.org/abs/2105.03824>`__ by James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, Santiago
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Ontanon.
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30. :doc:`Funnel Transformer <model_doc/funnel>` (from CMU/Google Brain) released with the paper `Funnel-Transformer:
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Filtering out Sequential Redundancy for Efficient Language Processing <https://arxiv.org/abs/2006.03236>`__ by
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Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le.
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57. :doc:`RoFormer <model_doc/roformer>` (from ZhuiyiTechnology), released together with the paper a `RoFormer:
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Enhanced Transformer with Rotary Position Embedding <https://arxiv.org/pdf/2104.09864v1.pdf>`__ by Jianlin Su and
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Yu Lu and Shengfeng Pan and Bo Wen and Yunfeng Liu.
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58. `SpeechEncoderDecoder <https://huggingface.co/transformers/master/model_doc/speechencoderdecoder.html>`__
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58. :doc:`SpeechEncoderDecoder <model_doc/speechencoderdecoder>`
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59. :doc:`SpeechToTextTransformer <model_doc/speech_to_text>` (from Facebook), released together with the paper
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`fairseq S2T: Fast Speech-to-Text Modeling with fairseq <https://arxiv.org/abs/2010.05171>`__ by Changhan Wang, Yun
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Tang, Xutai Ma, Anne Wu, Dmytro Okhonko, Juan Pino.
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60. `SpeechToTextTransformer2 <https://huggingface.co/transformers/master/model_doc/speech_to_text_2.html>`__ (from
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Facebook), released together with the paper `Large-Scale Self- and Semi-Supervised Learning for Speech Translation
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<https://arxiv.org/abs/2104.06678>`__ by Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis
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Conneau.
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60. :doc:`SpeechToTextTransformer2 <model_doc/speech_to_text_2>` (from Facebook), released together with the paper
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`Large-Scale Self- and Semi-Supervised Learning for Speech Translation <https://arxiv.org/abs/2104.06678>`__ by
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Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis Conneau.
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61. :doc:`Splinter <model_doc/splinter>` (from Tel Aviv University), released together with the paper `Few-Shot
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Question Answering by Pretraining Span Selection <https://arxiv.org/abs/2101.00438>`__ by Ori Ram, Yuval Kirstain,
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Jonathan Berant, Amir Globerson, Omer Levy.

‎examples/flax/question-answering/run_qa.py

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logger = logging.getLogger(__name__)
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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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check_min_version("4.11.0.dev0")
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check_min_version("4.11.0")
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Array = Any
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Dataset = datasets.arrow_dataset.Dataset

‎examples/flax/token-classification/run_flax_ner.py

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logger = logging.getLogger(__name__)
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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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check_min_version("4.11.0.dev0")
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check_min_version("4.11.0")
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/token-classification/requirements.txt")
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‎examples/pytorch/image-classification/run_image_classification.py

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logger = logging.getLogger(__name__)
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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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check_min_version("4.10.0.dev0")
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check_min_version("4.11.0")
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")
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‎examples/pytorch/language-modeling/run_clm.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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check_min_version("4.11.0")
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")
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‎examples/pytorch/language-modeling/run_mlm.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")
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‎examples/pytorch/language-modeling/run_plm.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/multiple-choice/run_swag.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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check_min_version("4.11.0.dev0")
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‎examples/pytorch/question-answering/run_qa.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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check_min_version("4.11.0.dev0")
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check_min_version("4.11.0")
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
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‎examples/pytorch/question-answering/run_qa_beam_search.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
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‎examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/question-answering/run_qa_no_trainer.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/speech-recognition/run_speech_recognition_ctc.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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require_version("datasets>=1.12.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")

‎examples/pytorch/summarization/run_summarization.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/text-classification/run_glue.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/text-classification/run_xnli.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/token-classification/run_ner.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/pytorch/translation/run_translation.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/translation/requirements.txt")
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‎examples/tensorflow/multiple-choice/run_swag.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/tensorflow/question-answering/run_qa.py

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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎examples/tensorflow/summarization/run_summarization.py

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# region Checking dependencies
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‎examples/tensorflow/text-classification/run_glue.py

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‎examples/tensorflow/translation/run_translation.py

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# region Dependencies and constants
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# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
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‎setup.py

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setup(
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version="4.11.0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
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author="Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Sam Shleifer, Patrick von Platen, Sylvain Gugger, Suraj Patil, Stas Bekman, Google AI Language Team Authors, Open AI team Authors, Facebook AI Authors, Carnegie Mellon University Authors",
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author_email="thomas@huggingface.co",
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description="State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",

‎src/transformers/__init__.py

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__version__ = "4.11.0"
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# Work around to update TensorFlow's absl.logging threshold which alters the
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# default Python logging output behavior when present.

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