v4.29.0.dev0
This commit is contained in:
Sylvain Gugger
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README.md
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README.md
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@ -310,7 +310,7 @@ Current number of checkpoints: ** (from Facebook AI) released with the paper [A ConvNet for the 2020s](https://arxiv.org/abs/2201.03545) by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie.
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1. **[ConvNeXTV2](https://huggingface.co/docs/transformers/model_doc/convnextv2)** (from Facebook AI) released with the paper [ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders](https://arxiv.org/abs/2301.00808) by Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie.
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1. **[CPM](https://huggingface.co/docs/transformers/model_doc/cpm)** (from Tsinghua University) released with the paper [CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://arxiv.org/abs/2012.00413) by Zhengyan Zhang, Xu Han, Hao Zhou, Pei Ke, Yuxian Gu, Deming Ye, Yujia Qin, Yusheng Su, Haozhe Ji, Jian Guan, Fanchao Qi, Xiaozhi Wang, Yanan Zheng, Guoyang Zeng, Huanqi Cao, Shengqi Chen, Daixuan Li, Zhenbo Sun, Zhiyuan Liu, Minlie Huang, Wentao Han, Jie Tang, Juanzi Li, Xiaoyan Zhu, Maosong Sun.
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1. **[CPM-Ant](https://huggingface.co/docs/transformers/main/model_doc/cpmant)** (from OpenBMB) released by the [OpenBMB](https://www.openbmb.org/).
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1. **[CPM-Ant](https://huggingface.co/docs/transformers/model_doc/cpmant)** (from OpenBMB) released by the [OpenBMB](https://www.openbmb.org/).
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1. **[CTRL](https://huggingface.co/docs/transformers/model_doc/ctrl)** (from Salesforce) released with the paper [CTRL: A Conditional Transformer Language Model for Controllable Generation](https://arxiv.org/abs/1909.05858) by Nitish Shirish Keskar*, Bryan McCann*, Lav R. Varshney, Caiming Xiong and Richard Socher.
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1. **[CvT](https://huggingface.co/docs/transformers/model_doc/cvt)** (from Microsoft) released with the paper [CvT: Introducing Convolutions to Vision Transformers](https://arxiv.org/abs/2103.15808) by Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, Lei Zhang.
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1. **[Data2Vec](https://huggingface.co/docs/transformers/model_doc/data2vec)** (from Facebook) released with the paper [Data2Vec: A General Framework for Self-supervised Learning in Speech, Vision and Language](https://arxiv.org/abs/2202.03555) by Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, Michael Auli.
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@ -319,7 +319,7 @@ Current number of checkpoints: ** (from Berkeley/Facebook/Google) released with the paper [Decision Transformer: Reinforcement Learning via Sequence Modeling](https://arxiv.org/abs/2106.01345) by Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch.
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1. **[Deformable DETR](https://huggingface.co/docs/transformers/model_doc/deformable_detr)** (from SenseTime Research) released with the paper [Deformable DETR: Deformable Transformers for End-to-End Object Detection](https://arxiv.org/abs/2010.04159) by Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai.
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1. **[DeiT](https://huggingface.co/docs/transformers/model_doc/deit)** (from Facebook) released with the paper [Training data-efficient image transformers & distillation through attention](https://arxiv.org/abs/2012.12877) by Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, Hervé Jégou.
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1. **[DePlot](https://huggingface.co/docs/transformers/main/model_doc/deplot)** (from Google AI) released with the paper [DePlot: One-shot visual language reasoning by plot-to-table translation](https://arxiv.org/abs/2212.10505) by Fangyu Liu, Julian Martin Eisenschlos, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Wenhu Chen, Nigel Collier, Yasemin Altun.
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1. **[DePlot](https://huggingface.co/docs/transformers/model_doc/deplot)** (from Google AI) released with the paper [DePlot: One-shot visual language reasoning by plot-to-table translation](https://arxiv.org/abs/2212.10505) by Fangyu Liu, Julian Martin Eisenschlos, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Wenhu Chen, Nigel Collier, Yasemin Altun.
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1. **[DETA](https://huggingface.co/docs/transformers/model_doc/deta)** (from The University of Texas at Austin) released with the paper [NMS Strikes Back](https://arxiv.org/abs/2212.06137) by Jeffrey Ouyang-Zhang, Jang Hyun Cho, Xingyi Zhou, Philipp Krähenbühl.
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1. **[DETR](https://huggingface.co/docs/transformers/model_doc/detr)** (from Facebook) released with the paper [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) by Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko.
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1. **[DialoGPT](https://huggingface.co/docs/transformers/model_doc/dialogpt)** (from Microsoft Research) released with the paper [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://arxiv.org/abs/1911.00536) by Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, Bill Dolan.
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@ -351,7 +351,7 @@ Current number of checkpoints: ** (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**.
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1. **[GPT-J](https://huggingface.co/docs/transformers/model_doc/gptj)** (from EleutherAI) released in the repository [kingoflolz/mesh-transformer-jax](https://github.com/kingoflolz/mesh-transformer-jax/) by Ben Wang and Aran Komatsuzaki.
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1. **[GPT-Sw3](https://huggingface.co/docs/transformers/model_doc/gpt-sw3)** (from AI-Sweden) released with the paper [Lessons Learned from GPT-SW3: Building the First Large-Scale Generative Language Model for Swedish](http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.376.pdf) by Ariel Ekgren, Amaru Cuba Gyllensten, Evangelia Gogoulou, Alice Heiman, Severine Verlinden, Joey Öhman, Fredrik Carlsson, Magnus Sahlgren.
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1. **[GPTBigCode](https://huggingface.co/docs/transformers/main/model_doc/gpt_bigcode)** (from BigCode) released with the paper [SantaCoder: don't reach for the stars!](https://arxiv.org/abs/2301.03988) by Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Munoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, Logesh Kumar Umapathi, Carolyn Jane Anderson, Yangtian Zi, Joel Lamy Poirier, Hailey Schoelkopf, Sergey Troshin, Dmitry Abulkhanov, Manuel Romero, Michael Lappert, Francesco De Toni, Bernardo García del Río, Qian Liu, Shamik Bose, Urvashi Bhattacharyya, Terry Yue Zhuo, Ian Yu, Paulo Villegas, Marco Zocca, Sourab Mangrulkar, David Lansky, Huu Nguyen, Danish Contractor, Luis Villa, Jia Li, Dzmitry Bahdanau, Yacine Jernite, Sean Hughes, Daniel Fried, Arjun Guha, Harm de Vries, Leandro von Werra.
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1. **[GPTBigCode](https://huggingface.co/docs/transformers/model_doc/gpt_bigcode)** (from BigCode) released with the paper [SantaCoder: don't reach for the stars!](https://arxiv.org/abs/2301.03988) by Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Munoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, Logesh Kumar Umapathi, Carolyn Jane Anderson, Yangtian Zi, Joel Lamy Poirier, Hailey Schoelkopf, Sergey Troshin, Dmitry Abulkhanov, Manuel Romero, Michael Lappert, Francesco De Toni, Bernardo García del Río, Qian Liu, Shamik Bose, Urvashi Bhattacharyya, Terry Yue Zhuo, Ian Yu, Paulo Villegas, Marco Zocca, Sourab Mangrulkar, David Lansky, Huu Nguyen, Danish Contractor, Luis Villa, Jia Li, Dzmitry Bahdanau, Yacine Jernite, Sean Hughes, Daniel Fried, Arjun Guha, Harm de Vries, Leandro von Werra.
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1. **[GPTSAN-japanese](https://huggingface.co/docs/transformers/model_doc/gptsan-japanese)** released in the repository [tanreinama/GPTSAN](https://github.com/tanreinama/GPTSAN/blob/main/report/model.md) by Toshiyuki Sakamoto(tanreinama).
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1. **[Graphormer](https://huggingface.co/docs/transformers/model_doc/graphormer)** (from Microsoft) released with the paper [Do Transformers Really Perform Bad for Graph Representation?](https://arxiv.org/abs/2106.05234) by Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu.
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1. **[GroupViT](https://huggingface.co/docs/transformers/model_doc/groupvit)** (from UCSD, NVIDIA) released with the paper [GroupViT: Semantic Segmentation Emerges from Text Supervision](https://arxiv.org/abs/2202.11094) by Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, Xiaolong Wang.
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@ -367,7 +367,7 @@ Current number of checkpoints: ** (from AllenAI) released with the paper [Longformer: The Long-Document Transformer](https://arxiv.org/abs/2004.05150) by Iz Beltagy, Matthew E. Peters, Arman Cohan.
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1. **[LeViT](https://huggingface.co/docs/transformers/model_doc/levit)** (from Meta AI) released with the paper [LeViT: A Vision Transformer in ConvNet's Clothing for Faster Inference](https://arxiv.org/abs/2104.01136) by Ben Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze.
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1. **[LiLT](https://huggingface.co/docs/transformers/model_doc/lilt)** (from South China University of Technology) released with the paper [LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding](https://arxiv.org/abs/2202.13669) by Jiapeng Wang, Lianwen Jin, Kai Ding.
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1. **[LLaMA](https://huggingface.co/docs/transformers/main/model_doc/llama)** (from The FAIR team of Meta AI) released with the paper [LLaMA: Open and Efficient Foundation Language Models](https://arxiv.org/abs/2302.13971) by Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, Guillaume Lample.
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1. **[LLaMA](https://huggingface.co/docs/transformers/model_doc/llama)** (from The FAIR team of Meta AI) released with the paper [LLaMA: Open and Efficient Foundation Language Models](https://arxiv.org/abs/2302.13971) by Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, Guillaume Lample.
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1. **[Longformer](https://huggingface.co/docs/transformers/model_doc/longformer)** (from AllenAI) released with the paper [Longformer: The Long-Document Transformer](https://arxiv.org/abs/2004.05150) by Iz Beltagy, Matthew E. Peters, Arman Cohan.
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1. **[LongT5](https://huggingface.co/docs/transformers/model_doc/longt5)** (from Google AI) released with the paper [LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://arxiv.org/abs/2112.07916) by Mandy Guo, Joshua Ainslie, David Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, Yinfei Yang.
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1. **[LUKE](https://huggingface.co/docs/transformers/model_doc/luke)** (from Studio Ousia) released with the paper [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://arxiv.org/abs/2010.01057) by Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, Yuji Matsumoto.
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@ -378,10 +378,10 @@ Current number of checkpoints: ** (from Microsoft Research Asia) released with the paper [MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding](https://arxiv.org/abs/2110.08518) by Junlong Li, Yiheng Xu, Lei Cui, Furu Wei.
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1. **[Mask2Former](https://huggingface.co/docs/transformers/model_doc/mask2former)** (from FAIR and UIUC) released with the paper [Masked-attention Mask Transformer for Universal Image Segmentation](https://arxiv.org/abs/2112.01527) by Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar.
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1. **[MaskFormer](https://huggingface.co/docs/transformers/model_doc/maskformer)** (from Meta and UIUC) released with the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) by Bowen Cheng, Alexander G. Schwing, Alexander Kirillov.
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1. **[MatCha](https://huggingface.co/docs/transformers/main/model_doc/matcha)** (from Google AI) released with the paper [MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering](https://arxiv.org/abs/2212.09662) by Fangyu Liu, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Yasemin Altun, Nigel Collier, Julian Martin Eisenschlos.
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1. **[MatCha](https://huggingface.co/docs/transformers/model_doc/matcha)** (from Google AI) released with the paper [MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering](https://arxiv.org/abs/2212.09662) by Fangyu Liu, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Yasemin Altun, Nigel Collier, Julian Martin Eisenschlos.
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1. **[mBART](https://huggingface.co/docs/transformers/model_doc/mbart)** (from Facebook) released with the paper [Multilingual Denoising Pre-training for Neural Machine Translation](https://arxiv.org/abs/2001.08210) by Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, Luke Zettlemoyer.
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1. **[mBART-50](https://huggingface.co/docs/transformers/model_doc/mbart)** (from Facebook) released with the paper [Multilingual Translation with Extensible Multilingual Pretraining and Finetuning](https://arxiv.org/abs/2008.00401) by Yuqing Tang, Chau Tran, Xian Li, Peng-Jen Chen, Naman Goyal, Vishrav Chaudhary, Jiatao Gu, Angela Fan.
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1. **[MEGA](https://huggingface.co/docs/transformers/main/model_doc/mega)** (from Facebook) released with the paper [Mega: Moving Average Equipped Gated Attention](https://arxiv.org/abs/2209.10655) by Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, and Luke Zettlemoyer.
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1. **[MEGA](https://huggingface.co/docs/transformers/model_doc/mega)** (from Facebook) released with the paper [Mega: Moving Average Equipped Gated Attention](https://arxiv.org/abs/2209.10655) by Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, and Luke Zettlemoyer.
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1. **[Megatron-BERT](https://huggingface.co/docs/transformers/model_doc/megatron-bert)** (from NVIDIA) released with the paper [Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism](https://arxiv.org/abs/1909.08053) by Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper and Bryan Catanzaro.
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1. **[Megatron-GPT2](https://huggingface.co/docs/transformers/model_doc/megatron_gpt2)** (from NVIDIA) released with the paper [Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism](https://arxiv.org/abs/1909.08053) by Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper and Bryan Catanzaro.
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1. **[MGP-STR](https://huggingface.co/docs/transformers/model_doc/mgp-str)** (from Alibaba Research) released with the paper [Multi-Granularity Prediction for Scene Text Recognition](https://arxiv.org/abs/2209.03592) by Peng Wang, Cheng Da, and Cong Yao.
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@ -396,7 +396,7 @@ Current number of checkpoints: ** (from SHI Labs) released with the paper [Neighborhood Attention Transformer](https://arxiv.org/abs/2204.07143) by Ali Hassani, Steven Walton, Jiachen Li, Shen Li, and Humphrey Shi.
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1. **[Nezha](https://huggingface.co/docs/transformers/model_doc/nezha)** (from Huawei Noah’s Ark Lab) released with the paper [NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204) by Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen and Qun Liu.
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1. **[NLLB](https://huggingface.co/docs/transformers/model_doc/nllb)** (from Meta) released with the paper [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672) by the NLLB team.
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1. **[NLLB-MOE](https://huggingface.co/docs/transformers/main/model_doc/nllb-moe)** (from Meta) released with the paper [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672) by the NLLB team.
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1. **[NLLB-MOE](https://huggingface.co/docs/transformers/model_doc/nllb-moe)** (from Meta) released with the paper [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672) by the NLLB team.
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1. **[Nyströmformer](https://huggingface.co/docs/transformers/model_doc/nystromformer)** (from the University of Wisconsin - Madison) released with the paper [Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention](https://arxiv.org/abs/2102.03902) by Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh.
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1. **[OneFormer](https://huggingface.co/docs/transformers/model_doc/oneformer)** (from SHI Labs) released with the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jitesh Jain, Jiachen Li, MangTik Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi.
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1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (from Meta AI) released with the paper [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
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@ -405,7 +405,7 @@ Current number of checkpoints: ** (from Google) released with the paper [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347) by Jason Phang, Yao Zhao, and Peter J. Liu.
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1. **[Perceiver IO](https://huggingface.co/docs/transformers/model_doc/perceiver)** (from Deepmind) released with the paper [Perceiver IO: A General Architecture for Structured Inputs & Outputs](https://arxiv.org/abs/2107.14795) by Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira.
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1. **[PhoBERT](https://huggingface.co/docs/transformers/model_doc/phobert)** (from VinAI Research) released with the paper [PhoBERT: Pre-trained language models for Vietnamese](https://www.aclweb.org/anthology/2020.findings-emnlp.92/) by Dat Quoc Nguyen and Anh Tuan Nguyen.
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1. **[Pix2Struct](https://huggingface.co/docs/transformers/main/model_doc/pix2struct)** (from Google) released with the paper [Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding](https://arxiv.org/abs/2210.03347) by Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova.
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1. **[Pix2Struct](https://huggingface.co/docs/transformers/model_doc/pix2struct)** (from Google) released with the paper [Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding](https://arxiv.org/abs/2210.03347) by Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova.
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1. **[PLBart](https://huggingface.co/docs/transformers/model_doc/plbart)** (from UCLA NLP) released with the paper [Unified Pre-training for Program Understanding and Generation](https://arxiv.org/abs/2103.06333) by Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang.
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1. **[PoolFormer](https://huggingface.co/docs/transformers/model_doc/poolformer)** (from Sea AI Labs) released with the paper [MetaFormer is Actually What You Need for Vision](https://arxiv.org/abs/2111.11418) by Yu, Weihao and Luo, Mi and Zhou, Pan and Si, Chenyang and Zhou, Yichen and Wang, Xinchao and Feng, Jiashi and Yan, Shuicheng.
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1. **[ProphetNet](https://huggingface.co/docs/transformers/model_doc/prophetnet)** (from Microsoft Research) released with the paper [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://arxiv.org/abs/2001.04063) by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.
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@ -61,7 +61,7 @@ from transformers.utils import check_min_version, get_full_repo_name, send_examp
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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("4.28.0.dev0")
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check_min_version("4.29.0.dev0")
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Array = Any
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Dataset = datasets.arrow_dataset.Dataset
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@ -54,7 +54,7 @@ from transformers.utils import check_min_version, get_full_repo_name, send_examp
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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("4.28.0.dev0")
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check_min_version("4.29.0.dev0")
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Array = Any
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Dataset = datasets.arrow_dataset.Dataset
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@ -55,7 +55,7 @@ from transformers.utils.versions import require_version
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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("4.28.0.dev0")
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check_min_version("4.29.0.dev0")
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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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@ -45,7 +45,7 @@ from transformers.utils.versions import require_version
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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("4.28.0.dev0")
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check_min_version("4.29.0.dev0")
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require_version("datasets>=1.14.0", "To fix: pip install -r examples/pytorch/audio-classification/requirements.txt")
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@ -54,7 +54,7 @@ from transformers.utils.versions import require_version
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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("4.28.0.dev0")
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check_min_version("4.29.0.dev0")
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||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/contrastive-image-text/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/image-classification/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -43,7 +43,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/image-pretraining/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -48,7 +48,7 @@ Any model supported by the AutoModelForMaskedImageModeling API can be used.
|
|||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
|
||||
check_min_version("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/image-pretraining/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -47,7 +47,7 @@ from transformers.utils import PaddingStrategy, check_min_version, send_example_
|
|||
|
||||
|
||||
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
|
||||
check_min_version("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -56,7 +56,7 @@ from transformers.utils import PaddingStrategy, check_min_version, get_full_repo
|
|||
|
||||
|
||||
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
|
||||
check_min_version("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
# You should update this to your particular problem to have better documentation of `model_type`
|
||||
|
|
|
|||
|
|
@ -49,7 +49,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -56,7 +56,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -51,7 +51,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=2.0.0", "To fix: pip install -r examples/pytorch/semantic-segmentation/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.18.0", "To fix: pip install -r examples/pytorch/speech-recognition/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.18.0", "To fix: pip install -r examples/pytorch/speech-recognition/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -52,7 +52,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -56,7 +56,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -49,7 +49,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/token-classification/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/token-classification/requirements.txt")
|
||||
|
|
|
|||
|
|
@ -52,7 +52,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/translation/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/translation/requirements.txt")
|
||||
|
|
|
|||
|
|
@ -51,7 +51,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version(
|
||||
"datasets>=1.8.0", "To fix: pip install -r examples/tensorflow/contrastive-image-text/requirements.txt"
|
||||
|
|
|
|||
|
|
@ -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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/image-classification/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -50,7 +50,7 @@ from transformers.utils import PaddingStrategy, check_min_version, send_example_
|
|||
|
||||
|
||||
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
|
||||
check_min_version("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -48,7 +48,7 @@ from transformers.utils import CONFIG_NAME, TF2_WEIGHTS_NAME, check_min_version,
|
|||
|
||||
|
||||
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
|
||||
check_min_version("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")
|
||||
|
||||
|
|
|
|||
|
|
@ -47,7 +47,7 @@ from transformers.utils import check_min_version, send_example_telemetry
|
|||
|
||||
|
||||
# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
|
||||
check_min_version("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
task_to_keys = {
|
||||
"cola": ("sentence", None),
|
||||
|
|
|
|||
|
|
@ -56,7 +56,7 @@ 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("4.28.0.dev0")
|
||||
check_min_version("4.29.0.dev0")
|
||||
|
||||
require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")
|
||||
|
||||
|
|
|
|||
2
setup.py
2
setup.py
|
|
@ -425,7 +425,7 @@ install_requires = [
|
|||
|
||||
setup(
|
||||
name="transformers",
|
||||
version="4.28.0.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="4.29.0.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)
|
||||
author="The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors)",
|
||||
author_email="transformers@huggingface.co",
|
||||
description="State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow",
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@
|
|||
# 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__ = "4.28.0.dev0"
|
||||
__version__ = "4.29.0.dev0"
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue