Release: v4.11.0
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Lysandre
2021-09-27 14:14:09 -04:00
parent 1c96500088
commit dc193c906d
27 changed files with 36 additions and 36 deletions

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@@ -238,7 +238,7 @@ Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
1. **[SpeechEncoderDecoder](https://huggingface.co/transformers/master/model_doc/speechencoderdecoder.html)**
1. **[SpeechEncoderDecoder](https://huggingface.co/transformers/model_doc/speechencoderdecoder.html)**
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.
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.
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.
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.
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.
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.

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@@ -27,7 +27,8 @@ author = "huggingface"
# The short X.Y version
version = ""
# The full version, including alpha/beta/rc tags
release = "4.11.0.dev0"
release = "4.11.0"

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@@ -185,9 +185,9 @@ Supported models
28. :doc:`FlauBERT <model_doc/flaubert>` (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.
29. `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.
29. :doc:`FNet <model_doc/fnet>` (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.
30. :doc:`Funnel Transformer <model_doc/funnel>` (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.
@@ -268,14 +268,13 @@ Supported models
57. :doc:`RoFormer <model_doc/roformer>` (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.
58. `SpeechEncoderDecoder <https://huggingface.co/transformers/master/model_doc/speechencoderdecoder.html>`__
58. :doc:`SpeechEncoderDecoder <model_doc/speechencoderdecoder>`
59. :doc:`SpeechToTextTransformer <model_doc/speech_to_text>` (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.
60. `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.
60. :doc:`SpeechToTextTransformer2 <model_doc/speech_to_text_2>` (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.
61. :doc:`Splinter <model_doc/splinter>` (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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@@ -57,7 +57,7 @@ from utils_qa import postprocess_qa_predictions
logger = logging.getLogger(__name__)
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
Array = Any
Dataset = datasets.arrow_dataset.Dataset

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@@ -50,7 +50,7 @@ from transformers.utils.versions import require_version
logger = logging.getLogger(__name__)
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/token-classification/requirements.txt")

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@@ -54,7 +54,7 @@ from transformers.utils.versions import require_version
logger = logging.getLogger(__name__)
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.10.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")

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@@ -51,7 +51,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

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@@ -50,7 +50,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

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@@ -46,7 +46,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

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@@ -47,7 +47,7 @@ from transformers.utils import check_min_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
logger = logging.getLogger(__name__)

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@@ -48,7 +48,7 @@ from utils_qa import postprocess_qa_predictions
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")

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@@ -47,7 +47,7 @@ from utils_qa import postprocess_qa_predictions_with_beam_search
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")

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@@ -54,7 +54,7 @@ from utils_qa import postprocess_qa_predictions_with_beam_search
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")

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@@ -56,7 +56,7 @@ from utils_qa import postprocess_qa_predictions
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")

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@@ -47,7 +47,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
# TODO(Patrick) Bump up as soon as audio features are merged
require_version("datasets>=1.12.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")

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@@ -48,7 +48,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")

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@@ -47,7 +47,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")

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@@ -47,7 +47,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")

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@@ -47,7 +47,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/token-classification/requirements.txt")

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@@ -51,7 +51,7 @@ from transformers.utils.versions import require_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/translation/requirements.txt")

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@@ -46,7 +46,7 @@ from transformers.utils import check_min_version
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
logger = logging.getLogger(__name__)

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@@ -45,7 +45,7 @@ from utils_qa import postprocess_qa_predictions
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
logger = logging.getLogger(__name__)

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@@ -51,7 +51,7 @@ from transformers.utils.versions import require_version
# region Checking dependencies
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")

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@@ -100,7 +100,7 @@ class SavePretrainedCallback(tf.keras.callbacks.Callback):
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
task_to_keys = {
"cola": ("sentence", None),

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@@ -53,7 +53,7 @@ from transformers.utils.versions import require_version
# region Dependencies and constants
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
check_min_version("4.11.0.dev0")
check_min_version("4.11.0")
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")

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@@ -344,7 +344,7 @@ install_requires = [
setup(
name="transformers",
version="4.11.0.dev0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
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)
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",
author_email="thomas@huggingface.co",
description="State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",

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@@ -22,7 +22,7 @@
# to defer the actual importing for when the objects are requested. This way `import transformers` provides the names
# in the namespace without actually importing anything (and especially none of the backends).
__version__ = "4.11.0.dev0"
__version__ = "4.11.0"
# Work around to update TensorFlow's absl.logging threshold which alters the
# default Python logging output behavior when present.