import{S as Oke,i as Wke,s as Fke,e as r,k as d,w as HL,t as l,M as Jke,c as a,d as t,m as s,a as n,x as ZL,h as o,b as i,N as Yke,f as AR,G as e,g as E,y as KL,L as Vke,q as zL,o as UL,B as qL,v as Xke}from"../chunks/vendor-hf-doc-builder.js";import{I as jL}from"../chunks/IconCopyLink-hf-doc-builder.js";function Hke(Eve){let 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ki=new jL({}),Oi=new jL({}),Wi=new jL({}),Ji=new jL({}),Ph=new jL({}),{c(){On=r("meta"),QL=d(),Wn=r("h1"),Kn=r("a"),Kp=r("span"),HL(ki.$$.fragment),LR=d(),zp=r("span"),RR=l("\u{1F917} Transformers"),$L=d(),jt=r("p"),bR=l("State-of-the-art Machine Learning for "),Pi=r("a"),SR=l("PyTorch"),wR=l(", "),Ni=r("a"),MR=l("TensorFlow"),GR=l(", and "),Ci=r("a"),kR=l("JAX"),PR=l("."),eR=d(),Wh=r("p"),NR=l("\u{1F917} Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities, such as:"),tR=d(),T=r("p"),CR=l("\u{1F4DD} "),Up=r("strong"),IR=l("Natural Language Processing"),BR=l(": text classification, named entity recognition, question answering, language modeling, summarization, translation, multiple choice, and text generation."),xR=r("br"),OR=l(`
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\u{1F5E3}\uFE0F `),jp=r("strong"),VR=l("Audio"),XR=l(": automatic speech recognition and audio classification."),HR=r("br"),ZR=l(`
\u{1F419} `),Qp=r("strong"),KR=l("Multimodal"),zR=l(": table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering."),rR=d(),Fh=r("p"),UR=l("\u{1F917} Transformers support framework interoperability between PyTorch, TensorFlow, and JAX. This provides the flexibility to use a different framework at each stage of a model\u2019s life; train a model in three lines of code in one framework, and load it for inference in another. Models can also be exported to a format like ONNX and TorchScript for deployment in production environments."),aR=d(),Qt=r("p"),qR=l("Join the growing community on the "),Ii=r("a"),jR=l("Hub"),QR=l(", "),Bi=r("a"),$R=l("forum"),eb=l(", or "),xi=r("a"),tb=l("Discord"),rb=l(" today!"),nR=d(),Fn=r("h2"),zn=r("a"),$p=r("span"),HL(Oi.$$.fragment),ab=d(),e8=r("span"),nb=l("If you are looking for custom support from the Hugging Face team"),lR=d(),Jn=r("a"),Gn=r("img"),lb=d(),oR=r("br"),iR=d(),Yn=r("h2"),Un=r("a"),t8=r("span"),HL(Wi.$$.fragment),ob=d(),r8=r("span"),ib=l("Contents"),dR=d(),Jh=r("p"),db=l("The documentation is organized into five sections:"),sR=d(),Ut=r("ul"),a8=r("li"),Yh=r("p"),n8=r("strong"),sb=l("GET STARTED"),hb=l(" provides a quick tour of the library and installation instructions to get up and running."),gb=d(),l8=r("li"),Vh=r("p"),o8=r("strong"),cb=l("TUTORIALS"),fb=l(" are a great place to start if you\u2019re a beginner. This section will help you gain the basic skills you need to start using the library."),ub=d(),i8=r("li"),Xh=r("p"),d8=r("strong"),vb=l("HOW-TO GUIDES"),Eb=l(" show you how to achieve a specific goal, like finetuning a pretrained model for language modeling or how to write and share a custom model."),Tb=d(),s8=r("li"),Hh=r("p"),h8=r("strong"),_b=l("CONCEPTUAL GUIDES"),mb=l(" offers more discussion and explanation of the underlying concepts and ideas behind models, tasks, and the design philosophy of \u{1F917} Transformers."),pb=d(),Fi=r("li"),Zh=r("p"),g8=r("strong"),Db=l("API"),yb=l(" describes all classes and functions:"),Ab=d(),Vn=r("ul"),Kh=r("li"),c8=r("strong"),Lb=l("MAIN CLASSES"),Rb=l(" details the most important classes like configuration, model, tokenizer, and pipeline."),bb=d(),zh=r("li"),f8=r("strong"),Sb=l("MODELS"),wb=l(" details the classes and functions related to each model implemented in the library."),Mb=d(),Uh=r("li"),u8=r("strong"),Gb=l("INTERNAL HELPERS"),kb=l(" details utility classes and functions used internally."),hR=d(),Xn=r("h3"),qn=r("a"),v8=r("span"),HL(Ji.$$.fragment),Pb=d(),E8=r("span"),Nb=l("Supported models"),gR=d(),h=r("ol"),jn=r("li"),T8=r("strong"),qh=r("a"),Cb=l("ALBERT"),Ib=l(" (from Google Research and the Toyota Technological Institute at Chicago) released with the paper "),Yi=r("a"),Bb=l("ALBERT: A Lite BERT for Self-supervised Learning of Language Representations"),xb=l(", by Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut."),Ob=d(),Qn=r("li"),_8=r("strong"),jh=r("a"),Wb=l("BART"),Fb=l(" (from Facebook) released with the paper "),Vi=r("a"),Jb=l("BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension"),Yb=l(" by Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov and Luke Zettlemoyer."),Vb=d(),$n=r("li"),m8=r("strong"),Qh=r("a"),Xb=l("BARThez"),Hb=l(" (from \xC9cole polytechnique) released with the paper "),Xi=r("a"),Zb=l("BARThez: a Skilled Pretrained French Sequence-to-Sequence Model"),Kb=l(" by Moussa Kamal Eddine, Antoine J.-P. Tixier, Michalis Vazirgiannis."),zb=d(),el=r("li"),p8=r("strong"),$h=r("a"),Ub=l("BARTpho"),qb=l(" (from VinAI Research) released with the paper "),Hi=r("a"),jb=l("BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese"),Qb=l(" by Nguyen Luong Tran, Duong Minh Le and Dat Quoc Nguyen."),$b=d(),tl=r("li"),D8=r("strong"),eg=r("a"),eS=l("BEiT"),tS=l(" (from Microsoft) released with the paper "),Zi=r("a"),rS=l("BEiT: BERT Pre-Training of Image Transformers"),aS=l(" by Hangbo Bao, Li Dong, Furu Wei."),nS=d(),rl=r("li"),y8=r("strong"),tg=r("a"),lS=l("BERT"),oS=l(" (from Google) released with the paper "),Ki=r("a"),iS=l("BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding"),dS=l(" by Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova."),sS=d(),al=r("li"),A8=r("strong"),rg=r("a"),hS=l("BERT For Sequence Generation"),gS=l(" (from Google) released with the paper "),zi=r("a"),cS=l("Leveraging Pre-trained Checkpoints for Sequence Generation Tasks"),fS=l(" by Sascha Rothe, Shashi Narayan, Aliaksei Severyn."),uS=d(),nl=r("li"),L8=r("strong"),ag=r("a"),vS=l("BERTweet"),ES=l(" (from VinAI Research) released with the paper "),Ui=r("a"),TS=l("BERTweet: A pre-trained language model for English Tweets"),_S=l(" by Dat Quoc Nguyen, Thanh Vu and Anh Tuan Nguyen."),mS=d(),ll=r("li"),R8=r("strong"),ng=r("a"),pS=l("BigBird-Pegasus"),DS=l(" (from Google Research) released with the paper "),qi=r("a"),yS=l("Big Bird: Transformers for Longer Sequences"),AS=l(" by Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed."),LS=d(),ol=r("li"),b8=r("strong"),lg=r("a"),RS=l("BigBird-RoBERTa"),bS=l(" (from Google Research) released with the paper "),ji=r("a"),SS=l("Big Bird: Transformers for Longer Sequences"),wS=l(" by Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed."),MS=d(),il=r("li"),S8=r("strong"),og=r("a"),GS=l("Blenderbot"),kS=l(" (from Facebook) released with the paper "),Qi=r("a"),PS=l("Recipes for building an open-domain chatbot"),NS=l(" by Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M. Smith, Y-Lan Boureau, Jason Weston."),CS=d(),dl=r("li"),w8=r("strong"),ig=r("a"),IS=l("BlenderbotSmall"),BS=l(" (from Facebook) released with the paper "),$i=r("a"),xS=l("Recipes for building an open-domain chatbot"),OS=l(" by Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M. Smith, Y-Lan Boureau, Jason Weston."),WS=d(),sl=r("li"),M8=r("strong"),dg=r("a"),FS=l("BLOOM"),JS=l(" (from BigScience workshop) released by the "),ed=r("a"),YS=l("BigSicence Workshop"),VS=l("."),XS=d(),hl=r("li"),G8=r("strong"),sg=r("a"),HS=l("BORT"),ZS=l(" (from Alexa) released with the paper "),td=r("a"),KS=l("Optimal Subarchitecture Extraction For BERT"),zS=l(" by Adrian de Wynter and Daniel J. Perry."),US=d(),gl=r("li"),k8=r("strong"),hg=r("a"),qS=l("ByT5"),jS=l(" (from Google Research) released with the paper "),rd=r("a"),QS=l("ByT5: Towards a token-free future with pre-trained byte-to-byte models"),$S=l(" by Linting Xue, Aditya Barua, Noah Constant, Rami Al-Rfou, Sharan Narang, Mihir Kale, Adam Roberts, Colin Raffel."),ew=d(),kn=r("li"),P8=r("strong"),gg=r("a"),tw=l("CamemBERT"),rw=l(" (from Inria/Facebook/Sorbonne) released with the paper "),ad=r("a"),aw=l("CamemBERT: a Tasty French Language Model"),nw=l(" by Louis Martin"),N8=r("em"),lw=l(", Benjamin Muller"),ow=l(", Pedro Javier Ortiz Su\xE1rez*, Yoann Dupont, Laurent Romary, \xC9ric Villemonte de la Clergerie, Djam\xE9 Seddah and Beno\xEEt Sagot."),iw=d(),cl=r("li"),C8=r("strong"),cg=r("a"),dw=l("CANINE"),sw=l(" (from Google Research) released with the paper "),nd=r("a"),hw=l("CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation"),gw=l(" by Jonathan H. Clark, Dan Garrette, Iulia Turc, John Wieting."),cw=d(),fl=r("li"),I8=r("strong"),fg=r("a"),fw=l("CLIP"),uw=l(" (from OpenAI) released with the paper "),ld=r("a"),vw=l("Learning Transferable Visual Models From Natural Language Supervision"),Ew=l(" by Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever."),Tw=d(),ul=r("li"),B8=r("strong"),ug=r("a"),_w=l("CodeGen"),mw=l(" (from Salesforce) released with the paper "),od=r("a"),pw=l("A Conversational Paradigm for Program Synthesis"),Dw=l(" by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong."),yw=d(),vl=r("li"),x8=r("strong"),vg=r("a"),Aw=l("Conditional DETR"),Lw=l(" (from Microsoft Research Asia) released with the paper "),id=r("a"),Rw=l("Conditional DETR for Fast Training Convergence"),bw=l(" by Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, Jingdong Wang."),Sw=d(),El=r("li"),O8=r("strong"),Eg=r("a"),ww=l("ConvBERT"),Mw=l(" (from YituTech) released with the paper "),dd=r("a"),Gw=l("ConvBERT: Improving BERT with Span-based Dynamic Convolution"),kw=l(" by Zihang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan."),Pw=d(),Tl=r("li"),W8=r("strong"),Tg=r("a"),Nw=l("ConvNeXT"),Cw=l(" (from Facebook AI) released with the paper "),sd=r("a"),Iw=l("A ConvNet for the 2020s"),Bw=l(" by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie."),xw=d(),_l=r("li"),F8=r("strong"),_g=r("a"),Ow=l("CPM"),Ww=l(" (from Tsinghua University) released with the paper "),hd=r("a"),Fw=l("CPM: A Large-scale Generative Chinese Pre-trained Language Model"),Jw=l(" 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."),Yw=d(),Pn=r("li"),J8=r("strong"),mg=r("a"),Vw=l("CTRL"),Xw=l(" (from Salesforce) released with the paper "),gd=r("a"),Hw=l("CTRL: A Conditional Transformer Language Model for Controllable Generation"),Zw=l(" by Nitish Shirish Keskar"),Y8=r("em"),Kw=l(", Bryan McCann"),zw=l(", Lav R. Varshney, Caiming Xiong and Richard Socher."),Uw=d(),ml=r("li"),V8=r("strong"),pg=r("a"),qw=l("CvT"),jw=l(" (from Microsoft) released with the paper "),cd=r("a"),Qw=l("CvT: Introducing Convolutions to Vision Transformers"),$w=l(" by Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, Lei Zhang."),eM=d(),pl=r("li"),X8=r("strong"),Dg=r("a"),tM=l("Data2Vec"),rM=l(" (from Facebook) released with the paper "),fd=r("a"),aM=l("Data2Vec:  A General Framework for Self-supervised Learning in Speech, Vision and Language"),nM=l(" by Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, Michael Auli."),lM=d(),Dl=r("li"),H8=r("strong"),yg=r("a"),oM=l("DeBERTa"),iM=l(" (from Microsoft) released with the paper "),ud=r("a"),dM=l("DeBERTa: Decoding-enhanced BERT with Disentangled Attention"),sM=l(" by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen."),hM=d(),yl=r("li"),Z8=r("strong"),Ag=r("a"),gM=l("DeBERTa-v2"),cM=l(" (from Microsoft) released with the paper "),vd=r("a"),fM=l("DeBERTa: Decoding-enhanced BERT with Disentangled Attention"),uM=l(" by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen."),vM=d(),Al=r("li"),K8=r("strong"),Lg=r("a"),EM=l("Decision Transformer"),TM=l(" (from Berkeley/Facebook/Google) released with the paper "),Ed=r("a"),_M=l("Decision Transformer: Reinforcement Learning via Sequence Modeling"),mM=l(" by Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch."),pM=d(),Ll=r("li"),z8=r("strong"),Rg=r("a"),DM=l("Deformable DETR"),yM=l(" (from SenseTime Research) released with the paper "),Td=r("a"),AM=l("Deformable DETR: Deformable Transformers for End-to-End Object Detection"),LM=l(" by Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai."),RM=d(),Rl=r("li"),U8=r("strong"),bg=r("a"),bM=l("DeiT"),SM=l(" (from Facebook) released with the paper "),_d=r("a"),wM=l("Training data-efficient image transformers & distillation through attention"),MM=l(" by Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, Herv\xE9 J\xE9gou."),GM=d(),bl=r("li"),q8=r("strong"),Sg=r("a"),kM=l("DETR"),PM=l(" (from Facebook) released with the paper "),md=r("a"),NM=l("End-to-End Object Detection with Transformers"),CM=l(" by Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko."),IM=d(),Sl=r("li"),j8=r("strong"),wg=r("a"),BM=l("DialoGPT"),xM=l(" (from Microsoft Research) released with the paper "),pd=r("a"),OM=l("DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation"),WM=l(" by Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, Bill Dolan."),FM=d(),qt=r("li"),Q8=r("strong"),Mg=r("a"),JM=l("DistilBERT"),YM=l(" (from HuggingFace), released together with the paper "),Dd=r("a"),VM=l("DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter"),XM=l(" by Victor Sanh, Lysandre Debut and Thomas Wolf. The same method has been applied to compress GPT2 into "),yd=r("a"),HM=l("DistilGPT2"),ZM=l(", RoBERTa into "),Ad=r("a"),KM=l("DistilRoBERTa"),zM=l(", Multilingual BERT into "),Ld=r("a"),UM=l("DistilmBERT"),qM=l(" and a German version of DistilBERT."),jM=d(),wl=r("li"),$8=r("strong"),Gg=r("a"),QM=l("DiT"),$M=l(" (from Microsoft Research) released with the paper "),Rd=r("a"),eG=l("DiT: Self-supervised Pre-training for Document Image Transformer"),tG=l(" by Junlong Li, Yiheng Xu, Tengchao Lv, Lei Cui, Cha Zhang, Furu Wei."),rG=d(),Ml=r("li"),e9=r("strong"),kg=r("a"),aG=l("Donut"),nG=l(" (from NAVER), released together with the paper "),bd=r("a"),lG=l("OCR-free Document Understanding Transformer"),oG=l(" by Geewook Kim, Teakgyu Hong, Moonbin Yim, Jeongyeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, Seunghyun Park."),iG=d(),Gl=r("li"),t9=r("strong"),Pg=r("a"),dG=l("DPR"),sG=l(" (from Facebook) released with the paper "),Sd=r("a"),hG=l("Dense Passage Retrieval for Open-Domain Question Answering"),gG=l(" by Vladimir Karpukhin, Barlas O\u011Fuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih."),cG=d(),kl=r("li"),r9=r("strong"),Ng=r("a"),fG=l("DPT"),uG=l(" (from Intel Labs) released with the paper "),wd=r("a"),vG=l("Vision Transformers for Dense Prediction"),EG=l(" by Ren\xE9 Ranftl, Alexey Bochkovskiy, Vladlen Koltun."),TG=d(),Pl=r("li"),a9=r("strong"),Cg=r("a"),_G=l("ELECTRA"),mG=l(" (from Google Research/Stanford University) released with the paper "),Md=r("a"),pG=l("ELECTRA: Pre-training text encoders as discriminators rather than generators"),DG=l(" by Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning."),yG=d(),Nl=r("li"),n9=r("strong"),Ig=r("a"),AG=l("EncoderDecoder"),LG=l(" (from Google Research) released with the paper "),Gd=r("a"),RG=l("Leveraging Pre-trained Checkpoints for Sequence Generation Tasks"),bG=l(" by Sascha Rothe, Shashi Narayan, Aliaksei Severyn."),SG=d(),Cl=r("li"),l9=r("strong"),Bg=r("a"),wG=l("ERNIE"),MG=l(" (from Baidu) released with the paper "),kd=r("a"),GG=l("ERNIE: Enhanced Representation through Knowledge Integration"),kG=l(" by Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, Hua Wu."),PG=d(),_=r("li"),o9=r("strong"),xg=r("a"),NG=l("ESM"),CG=l(" (from Meta AI) are transformer protein language models.  "),i9=r("strong"),IG=l("ESM-1b"),BG=l(" was released with the paper "),Pd=r("a"),xG=l("Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences"),OG=l(" by Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, and Rob Fergus. "),d9=r("strong"),WG=l("ESM-1v"),FG=l(" was released with the paper "),Nd=r("a"),JG=l("Language models enable zero-shot prediction of the effects of mutations on protein function"),YG=l(" by Joshua Meier, Roshan Rao, Robert Verkuil, Jason Liu, Tom Sercu and Alexander Rives. 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Keutzer."),_x=d(),zo=r("li"),SD=r("strong"),ef=r("a"),mx=l("Swin Transformer"),px=l(" (from Microsoft) released with the paper "),qs=r("a"),Dx=l("Swin Transformer: Hierarchical Vision Transformer using Shifted Windows"),yx=l(" by Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo."),Ax=d(),Uo=r("li"),wD=r("strong"),tf=r("a"),Lx=l("Swin Transformer V2"),Rx=l(" (from Microsoft) released with the paper "),js=r("a"),bx=l("Swin Transformer V2: Scaling Up Capacity and Resolution"),Sx=l(" by Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, Baining Guo."),wx=d(),qo=r("li"),MD=r("strong"),rf=r("a"),Mx=l("T5"),Gx=l(" (from Google AI) released with the paper "),Qs=r("a"),kx=l("Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"),Px=l(" 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. 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Tran, Xavier Garcia, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Neil Houlsby, Donald Metzler"),LO=d(),ni=r("li"),FD=r("strong"),uf=r("a"),RO=l("UniSpeech"),bO=l(" (from Microsoft Research) released with the paper "),ih=r("a"),SO=l("UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data"),wO=l(" by Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang."),MO=d(),li=r("li"),JD=r("strong"),vf=r("a"),GO=l("UniSpeechSat"),kO=l(" (from Microsoft Research) released with the paper "),dh=r("a"),PO=l("UNISPEECH-SAT: UNIVERSAL SPEECH REPRESENTATION LEARNING WITH SPEAKER AWARE PRE-TRAINING"),NO=l(" by Sanyuan Chen, Yu Wu, Chengyi Wang, Zhengyang Chen, Zhuo Chen, Shujie Liu, Jian Wu, Yao Qian, Furu Wei, Jinyu Li, Xiangzhan Yu."),CO=d(),oi=r("li"),YD=r("strong"),Ef=r("a"),IO=l("VAN"),BO=l(" (from Tsinghua University and Nankai University) released with the paper "),sh=r("a"),xO=l("Visual Attention Network"),OO=l(" by 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Zke={local:"transformers",sections:[{local:"if-you-are-looking-for-custom-support-from-the-hugging-face-team",title:"If you are looking for custom support from the Hugging Face team"},{local:"contents",sections:[{local:"supported-models",title:"Supported models"},{local:"supported-frameworks",title:"Supported frameworks"}],title:"Contents"}],title:"\u{1F917} Transformers"};function Kke(Eve){return Xke(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class qke extends Oke{constructor(On){super();Wke(this,On,Kke,Hke,Fke,{})}}export{qke as default,Zke as metadata};
