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Title: GitHub - echallenge/transformers: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Open Graph Title: GitHub - echallenge/transformers: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

X Title: GitHub - echallenge/transformers: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Description: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - echallenge/transformers

Open Graph Description: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - echallenge/transformers

X Description: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - echallenge/transformers

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https://patch-diff.githubusercontent.com/echallenge/transformers#----state-of-the-art-machine-learning-for-jax-pytorch-and-tensorflow
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https://patch-diff.githubusercontent.com/echallenge/transformers#----
model hubhttps://huggingface.co/models
Jaxhttps://jax.readthedocs.io/en/latest/
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https://patch-diff.githubusercontent.com/echallenge/transformers#online-demos
model hubhttps://huggingface.co/models
private model hosting, versioning, & an inference APIhttps://huggingface.co/pricing
Masked word completion with BERThttps://huggingface.co/bert-base-uncased?text=Paris+is+the+%5BMASK%5D+of+France
Name Entity Recognition with Electrahttps://huggingface.co/dbmdz/electra-large-discriminator-finetuned-conll03-english?text=My+name+is+Sarah+and+I+live+in+London+city
Text generation with GPT-2https://huggingface.co/gpt2?text=A+long+time+ago%2C+
Natural Language Inference with RoBERTahttps://huggingface.co/roberta-large-mnli?text=The+dog+was+lost.+Nobody+lost+any+animal
Summarization with BARThttps://huggingface.co/facebook/bart-large-cnn?text=The+tower+is+324+metres+%281%2C063+ft%29+tall%2C+about+the+same+height+as+an+81-storey+building%2C+and+the+tallest+structure+in+Paris.+Its+base+is+square%2C+measuring+125+metres+%28410+ft%29+on+each+side.+During+its+construction%2C+the+Eiffel+Tower+surpassed+the+Washington+Monument+to+become+the+tallest+man-made+structure+in+the+world%2C+a+title+it+held+for+41+years+until+the+Chrysler+Building+in+New+York+City+was+finished+in+1930.+It+was+the+first+structure+to+reach+a+height+of+300+metres.+Due+to+the+addition+of+a+broadcasting+aerial+at+the+top+of+the+tower+in+1957%2C+it+is+now+taller+than+the+Chrysler+Building+by+5.2+metres+%2817+ft%29.+Excluding+transmitters%2C+the+Eiffel+Tower+is+the+second+tallest+free-standing+structure+in+France+after+the+Millau+Viaduct
Question answering with DistilBERThttps://huggingface.co/distilbert-base-uncased-distilled-squad?text=Which+name+is+also+used+to+describe+the+Amazon+rainforest+in+English%3F&context=The+Amazon+rainforest+%28Portuguese%3A+Floresta+Amaz%C3%B4nica+or+Amaz%C3%B4nia%3B+Spanish%3A+Selva+Amaz%C3%B3nica%2C+Amazon%C3%ADa+or+usually+Amazonia%3B+French%3A+For%C3%AAt+amazonienne%3B+Dutch%3A+Amazoneregenwoud%29%2C+also+known+in+English+as+Amazonia+or+the+Amazon+Jungle%2C+is+a+moist+broadleaf+forest+that+covers+most+of+the+Amazon+basin+of+South+America.+This+basin+encompasses+7%2C000%2C000+square+kilometres+%282%2C700%2C000+sq+mi%29%2C+of+which+5%2C500%2C000+square+kilometres+%282%2C100%2C000+sq+mi%29+are+covered+by+the+rainforest.+This+region+includes+territory+belonging+to+nine+nations.+The+majority+of+the+forest+is+contained+within+Brazil%2C+with+60%25+of+the+rainforest%2C+followed+by+Peru+with+13%25%2C+Colombia+with+10%25%2C+and+with+minor+amounts+in+Venezuela%2C+Ecuador%2C+Bolivia%2C+Guyana%2C+Suriname+and+French+Guiana.+States+or+departments+in+four+nations+contain+%22Amazonas%22+in+their+names.+The+Amazon+represents+over+half+of+the+planet%27s+remaining+rainforests%2C+and+comprises+the+largest+and+most+biodiverse+tract+of+tropical+rainforest+in+the+world%2C+with+an+estimated+390+billion+individual+trees+divided+into+16%2C000+species
Translation with T5https://huggingface.co/t5-base?text=My+name+is+Wolfgang+and+I+live+in+Berlin
Image classification with ViThttps://huggingface.co/google/vit-base-patch16-224
Object Detection with DETRhttps://huggingface.co/facebook/detr-resnet-50
Semantic Segmentation with SegFormerhttps://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512
Panoptic Segmentation with DETRhttps://huggingface.co/facebook/detr-resnet-50-panoptic
Automatic Speech Recognition with Wav2Vec2https://huggingface.co/facebook/wav2vec2-base-960h
Keyword Spotting with Wav2Vec2https://huggingface.co/superb/wav2vec2-base-superb-ks
Visual Question Answering with ViLThttps://huggingface.co/dandelin/vilt-b32-finetuned-vqa
Write With Transformerhttps://transformer.huggingface.co
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https://patch-diff.githubusercontent.com/echallenge/transformers#quick-tour
https://camo.githubusercontent.com/4153c3f6ae91d9b2d21065c7ff7596b0e24b0c5c23febf3e66eb503324eed1d3/68747470733a2f2f68756767696e67666163652e636f2f64617461736574732f68756767696e67666163652f646f63756d656e746174696f6e2d696d616765732f7265736f6c76652f6d61696e2f636f636f5f73616d706c652e706e67
https://camo.githubusercontent.com/c8821fb97a1b525d5ea9b5f67057b37392c430ee7b5915b4d6ad481202f410a8/68747470733a2f2f68756767696e67666163652e636f2f64617461736574732f68756767696e67666163652f646f63756d656e746174696f6e2d696d616765732f7265736f6c76652f6d61696e2f636f636f5f73616d706c655f706f73745f70726f6365737365642e706e67
https://patch-diff.githubusercontent.com/echallenge/transformers#--------
this tutorialhttps://huggingface.co/docs/transformers/task_summary
Pytorch nn.Modulehttps://pytorch.org/docs/stable/nn.html#torch.nn.Module
TensorFlow tf.keras.Modelhttps://www.tensorflow.org/api_docs/python/tf/keras/Model
This tutorialhttps://huggingface.co/docs/transformers/training
https://patch-diff.githubusercontent.com/echallenge/transformers#why-should-i-use-transformers
https://patch-diff.githubusercontent.com/echallenge/transformers#why-shouldnt-i-use-transformers
Acceleratehttps://huggingface.co/docs/accelerate
examples folderhttps://github.com/huggingface/transformers/tree/main/examples
https://patch-diff.githubusercontent.com/echallenge/transformers#installation
https://patch-diff.githubusercontent.com/echallenge/transformers#with-pip
virtual environmenthttps://docs.python.org/3/library/venv.html
user guidehttps://packaging.python.org/guides/installing-using-pip-and-virtual-environments/
TensorFlow installation pagehttps://www.tensorflow.org/install/
PyTorch installation pagehttps://pytorch.org/get-started/locally/#start-locally
Flaxhttps://github.com/google/flax#quick-install
Jaxhttps://github.com/google/jax#installation
install the library from sourcehttps://huggingface.co/docs/transformers/installation#installing-from-source
https://patch-diff.githubusercontent.com/echallenge/transformers#with-conda
this issuehttps://github.com/huggingface/huggingface_hub/issues/1062
https://patch-diff.githubusercontent.com/echallenge/transformers#model-architectures
All the model checkpointshttps://huggingface.co/models
model hubhttps://huggingface.co
usershttps://huggingface.co/users
organizationshttps://huggingface.co/organizations
https://camo.githubusercontent.com/f36a36c84f2ff8605938db0f71595cdfebb5ebc941833aeb2591205f220bc9d2/68747470733a2f2f696d672e736869656c64732e696f2f656e64706f696e743f75726c3d68747470733a2f2f68756767696e67666163652e636f2f6170692f736869656c64732f6d6f64656c7326636f6c6f723d627269676874677265656e
herehttps://huggingface.co/docs/transformers/model_summary
ALBERThttps://huggingface.co/docs/transformers/model_doc/albert
ALBERT: A Lite BERT for Self-supervised Learning of Language Representationshttps://arxiv.org/abs/1909.11942
BARThttps://huggingface.co/docs/transformers/model_doc/bart
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensionhttps://arxiv.org/abs/1910.13461
BARThezhttps://huggingface.co/docs/transformers/model_doc/barthez
BARThez: a Skilled Pretrained French Sequence-to-Sequence Modelhttps://arxiv.org/abs/2010.12321
BARTphohttps://huggingface.co/docs/transformers/model_doc/bartpho
BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamesehttps://arxiv.org/abs/2109.09701
BEiThttps://huggingface.co/docs/transformers/model_doc/beit
BEiT: BERT Pre-Training of Image Transformershttps://arxiv.org/abs/2106.08254
BERThttps://huggingface.co/docs/transformers/model_doc/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understandinghttps://arxiv.org/abs/1810.04805
BERT For Sequence Generationhttps://huggingface.co/docs/transformers/model_doc/bert-generation
Leveraging Pre-trained Checkpoints for Sequence Generation Taskshttps://arxiv.org/abs/1907.12461
BERTweethttps://huggingface.co/docs/transformers/model_doc/bertweet
BERTweet: A pre-trained language model for English Tweetshttps://aclanthology.org/2020.emnlp-demos.2/
BigBird-Pegasushttps://huggingface.co/docs/transformers/model_doc/bigbird_pegasus
Big Bird: Transformers for Longer Sequenceshttps://arxiv.org/abs/2007.14062
BigBird-RoBERTahttps://huggingface.co/docs/transformers/model_doc/big_bird
Big Bird: Transformers for Longer Sequenceshttps://arxiv.org/abs/2007.14062
Blenderbothttps://huggingface.co/docs/transformers/model_doc/blenderbot
Recipes for building an open-domain chatbothttps://arxiv.org/abs/2004.13637
BlenderbotSmallhttps://huggingface.co/docs/transformers/model_doc/blenderbot-small
Recipes for building an open-domain chatbothttps://arxiv.org/abs/2004.13637
BLOOMhttps://huggingface.co/docs/transformers/model_doc/bloom
BigSicence Workshophttps://bigscience.huggingface.co/
BORThttps://huggingface.co/docs/transformers/model_doc/bort
Optimal Subarchitecture Extraction For BERThttps://arxiv.org/abs/2010.10499
ByT5https://huggingface.co/docs/transformers/model_doc/byt5
ByT5: Towards a token-free future with pre-trained byte-to-byte modelshttps://arxiv.org/abs/2105.13626
CamemBERThttps://huggingface.co/docs/transformers/model_doc/camembert
CamemBERT: a Tasty French Language Modelhttps://arxiv.org/abs/1911.03894
CANINEhttps://huggingface.co/docs/transformers/model_doc/canine
CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representationhttps://arxiv.org/abs/2103.06874
CLIPhttps://huggingface.co/docs/transformers/model_doc/clip
Learning Transferable Visual Models From Natural Language Supervisionhttps://arxiv.org/abs/2103.00020
CLIPSeghttps://huggingface.co/docs/transformers/main/model_doc/clipseg
Image Segmentation Using Text and Image Promptshttps://arxiv.org/abs/2112.10003
CodeGenhttps://huggingface.co/docs/transformers/model_doc/codegen
A Conversational Paradigm for Program Synthesishttps://arxiv.org/abs/2203.13474
Conditional DETRhttps://huggingface.co/docs/transformers/model_doc/conditional_detr
Conditional DETR for Fast Training Convergencehttps://arxiv.org/abs/2108.06152
ConvBERThttps://huggingface.co/docs/transformers/model_doc/convbert
ConvBERT: Improving BERT with Span-based Dynamic Convolutionhttps://arxiv.org/abs/2008.02496
ConvNeXThttps://huggingface.co/docs/transformers/model_doc/convnext
A ConvNet for the 2020shttps://arxiv.org/abs/2201.03545
CPMhttps://huggingface.co/docs/transformers/model_doc/cpm
CPM: A Large-scale Generative Chinese Pre-trained Language Modelhttps://arxiv.org/abs/2012.00413
CTRLhttps://huggingface.co/docs/transformers/model_doc/ctrl
CTRL: A Conditional Transformer Language Model for Controllable Generationhttps://arxiv.org/abs/1909.05858
CvThttps://huggingface.co/docs/transformers/model_doc/cvt
CvT: Introducing Convolutions to Vision Transformershttps://arxiv.org/abs/2103.15808
Data2Vechttps://huggingface.co/docs/transformers/model_doc/data2vec
Data2Vec: A General Framework for Self-supervised Learning in Speech, Vision and Languagehttps://arxiv.org/abs/2202.03555
DeBERTahttps://huggingface.co/docs/transformers/model_doc/deberta
DeBERTa: Decoding-enhanced BERT with Disentangled Attentionhttps://arxiv.org/abs/2006.03654
DeBERTa-v2https://huggingface.co/docs/transformers/model_doc/deberta-v2
DeBERTa: Decoding-enhanced BERT with Disentangled Attentionhttps://arxiv.org/abs/2006.03654
Decision Transformerhttps://huggingface.co/docs/transformers/model_doc/decision_transformer
Decision Transformer: Reinforcement Learning via Sequence Modelinghttps://arxiv.org/abs/2106.01345
Deformable DETRhttps://huggingface.co/docs/transformers/model_doc/deformable_detr
Deformable DETR: Deformable Transformers for End-to-End Object Detectionhttps://arxiv.org/abs/2010.04159
DeiThttps://huggingface.co/docs/transformers/model_doc/deit
Training data-efficient image transformers & distillation through attentionhttps://arxiv.org/abs/2012.12877
DETRhttps://huggingface.co/docs/transformers/model_doc/detr
End-to-End Object Detection with Transformershttps://arxiv.org/abs/2005.12872
DialoGPThttps://huggingface.co/docs/transformers/model_doc/dialogpt
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationhttps://arxiv.org/abs/1911.00536
DistilBERThttps://huggingface.co/docs/transformers/model_doc/distilbert
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterhttps://arxiv.org/abs/1910.01108
DistilGPT2https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation
DistilRoBERTahttps://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation
DistilmBERThttps://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation
DiThttps://huggingface.co/docs/transformers/model_doc/dit
DiT: Self-supervised Pre-training for Document Image Transformerhttps://arxiv.org/abs/2203.02378
Donuthttps://huggingface.co/docs/transformers/model_doc/donut
OCR-free Document Understanding Transformerhttps://arxiv.org/abs/2111.15664
DPRhttps://huggingface.co/docs/transformers/model_doc/dpr
Dense Passage Retrieval for Open-Domain Question Answeringhttps://arxiv.org/abs/2004.04906
DPThttps://huggingface.co/docs/transformers/master/model_doc/dpt
Vision Transformers for Dense Predictionhttps://arxiv.org/abs/2103.13413
ELECTRAhttps://huggingface.co/docs/transformers/model_doc/electra
ELECTRA: Pre-training text encoders as discriminators rather than generatorshttps://arxiv.org/abs/2003.10555
EncoderDecoderhttps://huggingface.co/docs/transformers/model_doc/encoder-decoder
Leveraging Pre-trained Checkpoints for Sequence Generation Taskshttps://arxiv.org/abs/1907.12461
ERNIEhttps://huggingface.co/docs/transformers/model_doc/ernie
ERNIE: Enhanced Representation through Knowledge Integrationhttps://arxiv.org/abs/1904.09223
ESMhttps://huggingface.co/docs/transformers/model_doc/esm
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequenceshttps://www.pnas.org/content/118/15/e2016239118
Language models enable zero-shot prediction of the effects of mutations on protein functionhttps://doi.org/10.1101/2021.07.09.450648
Language models of protein sequences at the scale of evolution enable accurate structure predictionhttps://doi.org/10.1101/2022.07.20.500902
FLAN-T5https://huggingface.co/docs/transformers/model_doc/flan-t5
google-research/t5xhttps://github.com/google-research/t5x/blob/main/docs/models.md#flan-t5-checkpoints
FlauBERThttps://huggingface.co/docs/transformers/model_doc/flaubert
FlauBERT: Unsupervised Language Model Pre-training for Frenchhttps://arxiv.org/abs/1912.05372
FLAVAhttps://huggingface.co/docs/transformers/model_doc/flava
FLAVA: A Foundational Language And Vision Alignment Modelhttps://arxiv.org/abs/2112.04482
FNethttps://huggingface.co/docs/transformers/model_doc/fnet
FNet: Mixing Tokens with Fourier Transformshttps://arxiv.org/abs/2105.03824
Funnel Transformerhttps://huggingface.co/docs/transformers/model_doc/funnel
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processinghttps://arxiv.org/abs/2006.03236
GLPNhttps://huggingface.co/docs/transformers/model_doc/glpn
Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepthhttps://arxiv.org/abs/2201.07436
GPThttps://huggingface.co/docs/transformers/model_doc/openai-gpt
Improving Language Understanding by Generative Pre-Traininghttps://blog.openai.com/language-unsupervised/
GPT Neohttps://huggingface.co/docs/transformers/model_doc/gpt_neo
EleutherAI/gpt-neohttps://github.com/EleutherAI/gpt-neo
GPT NeoXhttps://huggingface.co/docs/transformers/model_doc/gpt_neox
GPT-NeoX-20B: An Open-Source Autoregressive Language Modelhttps://arxiv.org/abs/2204.06745
GPT NeoX Japanesehttps://huggingface.co/docs/transformers/model_doc/gpt_neox_japanese
GPT-2https://huggingface.co/docs/transformers/model_doc/gpt2
Language Models are Unsupervised Multitask Learnershttps://blog.openai.com/better-language-models/
GPT-Jhttps://huggingface.co/docs/transformers/model_doc/gptj
kingoflolz/mesh-transformer-jaxhttps://github.com/kingoflolz/mesh-transformer-jax/
GroupViThttps://huggingface.co/docs/transformers/model_doc/groupvit
GroupViT: Semantic Segmentation Emerges from Text Supervisionhttps://arxiv.org/abs/2202.11094
Huberthttps://huggingface.co/docs/transformers/model_doc/hubert
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitshttps://arxiv.org/abs/2106.07447
I-BERThttps://huggingface.co/docs/transformers/model_doc/ibert
I-BERT: Integer-only BERT Quantizationhttps://arxiv.org/abs/2101.01321
ImageGPThttps://huggingface.co/docs/transformers/model_doc/imagegpt
Generative Pretraining from Pixelshttps://openai.com/blog/image-gpt/
Jukeboxhttps://huggingface.co/docs/transformers/main/model_doc/jukebox
Jukebox: A Generative Model for Musichttps://arxiv.org/pdf/2005.00341.pdf
LayoutLMhttps://huggingface.co/docs/transformers/model_doc/layoutlm
LayoutLM: Pre-training of Text and Layout for Document Image Understandinghttps://arxiv.org/abs/1912.13318
LayoutLMv2https://huggingface.co/docs/transformers/model_doc/layoutlmv2
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understandinghttps://arxiv.org/abs/2012.14740
LayoutLMv3https://huggingface.co/docs/transformers/model_doc/layoutlmv3
LayoutLMv3: Pre-training for Document AI with Unified Text and Image Maskinghttps://arxiv.org/abs/2204.08387
LayoutXLMhttps://huggingface.co/docs/transformers/model_doc/layoutxlm
LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understandinghttps://arxiv.org/abs/2104.08836
LEDhttps://huggingface.co/docs/transformers/model_doc/led
Longformer: The Long-Document Transformerhttps://arxiv.org/abs/2004.05150
LeViThttps://huggingface.co/docs/transformers/model_doc/levit
LeViT: A Vision Transformer in ConvNet's Clothing for Faster Inferencehttps://arxiv.org/abs/2104.01136
LiLThttps://huggingface.co/docs/transformers/model_doc/lilt
LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understandinghttps://arxiv.org/abs/2202.13669
Longformerhttps://huggingface.co/docs/transformers/model_doc/longformer
Longformer: The Long-Document Transformerhttps://arxiv.org/abs/2004.05150
LongT5https://huggingface.co/docs/transformers/model_doc/longt5
LongT5: Efficient Text-To-Text Transformer for Long Sequenceshttps://arxiv.org/abs/2112.07916
LUKEhttps://huggingface.co/docs/transformers/model_doc/luke
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentionhttps://arxiv.org/abs/2010.01057
LXMERThttps://huggingface.co/docs/transformers/model_doc/lxmert
LXMERT: Learning Cross-Modality Encoder Representations from Transformers for Open-Domain Question Answeringhttps://arxiv.org/abs/1908.07490
M-CTC-Thttps://huggingface.co/docs/transformers/model_doc/mctct
Pseudo-Labeling For Massively Multilingual Speech Recognitionhttps://arxiv.org/abs/2111.00161
M2M100https://huggingface.co/docs/transformers/model_doc/m2m_100
Beyond English-Centric Multilingual Machine Translationhttps://arxiv.org/abs/2010.11125
MarianMThttps://huggingface.co/docs/transformers/model_doc/marian
OPUShttp://opus.nlpl.eu/
Marian Frameworkhttps://marian-nmt.github.io/
MarkupLMhttps://huggingface.co/docs/transformers/model_doc/markuplm
MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understandinghttps://arxiv.org/abs/2110.08518
MaskFormerhttps://huggingface.co/docs/transformers/model_doc/maskformer
Per-Pixel Classification is Not All You Need for Semantic Segmentationhttps://arxiv.org/abs/2107.06278
mBARThttps://huggingface.co/docs/transformers/model_doc/mbart
Multilingual Denoising Pre-training for Neural Machine Translationhttps://arxiv.org/abs/2001.08210
mBART-50https://huggingface.co/docs/transformers/model_doc/mbart
Multilingual Translation with Extensible Multilingual Pretraining and Finetuninghttps://arxiv.org/abs/2008.00401
Megatron-BERThttps://huggingface.co/docs/transformers/model_doc/megatron-bert
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelismhttps://arxiv.org/abs/1909.08053
Megatron-GPT2https://huggingface.co/docs/transformers/model_doc/megatron_gpt2
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelismhttps://arxiv.org/abs/1909.08053
mLUKEhttps://huggingface.co/docs/transformers/model_doc/mluke
mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Modelshttps://arxiv.org/abs/2110.08151
MobileBERThttps://huggingface.co/docs/transformers/model_doc/mobilebert
MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Deviceshttps://arxiv.org/abs/2004.02984
MobileNetV2https://huggingface.co/docs/transformers/model_doc/mobilenet_v2
MobileNetV2: Inverted Residuals and Linear Bottleneckshttps://arxiv.org/abs/1801.04381
MobileViThttps://huggingface.co/docs/transformers/model_doc/mobilevit
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformerhttps://arxiv.org/abs/2110.02178
MPNethttps://huggingface.co/docs/transformers/model_doc/mpnet
MPNet: Masked and Permuted Pre-training for Language Understandinghttps://arxiv.org/abs/2004.09297
MT5https://huggingface.co/docs/transformers/model_doc/mt5
mT5: A massively multilingual pre-trained text-to-text transformerhttps://arxiv.org/abs/2010.11934
MVPhttps://huggingface.co/docs/transformers/model_doc/mvp
MVP: Multi-task Supervised Pre-training for Natural Language Generationhttps://arxiv.org/abs/2206.12131
Nezhahttps://huggingface.co/docs/transformers/model_doc/nezha
NEZHA: Neural Contextualized Representation for Chinese Language Understandinghttps://arxiv.org/abs/1909.00204
NLLBhttps://huggingface.co/docs/transformers/model_doc/nllb
No Language Left Behind: Scaling Human-Centered Machine Translationhttps://arxiv.org/abs/2207.04672
Nyströmformerhttps://huggingface.co/docs/transformers/model_doc/nystromformer
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attentionhttps://arxiv.org/abs/2102.03902
OPThttps://huggingface.co/docs/transformers/master/model_doc/opt
OPT: Open Pre-trained Transformer Language Modelshttps://arxiv.org/abs/2205.01068
OWL-ViThttps://huggingface.co/docs/transformers/model_doc/owlvit
Simple Open-Vocabulary Object Detection with Vision Transformershttps://arxiv.org/abs/2205.06230
Pegasushttps://huggingface.co/docs/transformers/model_doc/pegasus
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationhttps://arxiv.org/abs/1912.08777
PEGASUS-Xhttps://huggingface.co/docs/transformers/model_doc/pegasus_x
Investigating Efficiently Extending Transformers for Long Input Summarizationhttps://arxiv.org/abs/2208.04347
Perceiver IOhttps://huggingface.co/docs/transformers/model_doc/perceiver
Perceiver IO: A General Architecture for Structured Inputs & Outputshttps://arxiv.org/abs/2107.14795
PhoBERThttps://huggingface.co/docs/transformers/model_doc/phobert
PhoBERT: Pre-trained language models for Vietnamesehttps://www.aclweb.org/anthology/2020.findings-emnlp.92/
PLBarthttps://huggingface.co/docs/transformers/model_doc/plbart
Unified Pre-training for Program Understanding and Generationhttps://arxiv.org/abs/2103.06333
PoolFormerhttps://huggingface.co/docs/transformers/model_doc/poolformer
MetaFormer is Actually What You Need for Visionhttps://arxiv.org/abs/2111.11418
ProphetNethttps://huggingface.co/docs/transformers/model_doc/prophetnet
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-traininghttps://arxiv.org/abs/2001.04063
QDQBerthttps://huggingface.co/docs/transformers/model_doc/qdqbert
Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluationhttps://arxiv.org/abs/2004.09602
RAGhttps://huggingface.co/docs/transformers/model_doc/rag
Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskshttps://arxiv.org/abs/2005.11401
REALMhttps://huggingface.co/docs/transformers/model_doc/realm.html
REALM: Retrieval-Augmented Language Model Pre-Traininghttps://arxiv.org/abs/2002.08909
Reformerhttps://huggingface.co/docs/transformers/model_doc/reformer
Reformer: The Efficient Transformerhttps://arxiv.org/abs/2001.04451
RegNethttps://huggingface.co/docs/transformers/model_doc/regnet
Designing Network Design Spacehttps://arxiv.org/abs/2003.13678
RemBERThttps://huggingface.co/docs/transformers/model_doc/rembert
Rethinking embedding coupling in pre-trained language modelshttps://arxiv.org/abs/2010.12821
ResNethttps://huggingface.co/docs/transformers/model_doc/resnet
Deep Residual Learning for Image Recognitionhttps://arxiv.org/abs/1512.03385
RoBERTahttps://huggingface.co/docs/transformers/model_doc/roberta
RoBERTa: A Robustly Optimized BERT Pretraining Approachhttps://arxiv.org/abs/1907.11692
RoCBerthttps://huggingface.co/docs/transformers/main/model_doc/roc_bert
RoCBert: Robust Chinese Bert with Multimodal Contrastive Pretraininghttps://aclanthology.org/2022.acl-long.65.pdf
RoFormerhttps://huggingface.co/docs/transformers/model_doc/roformer
RoFormer: Enhanced Transformer with Rotary Position Embeddinghttps://arxiv.org/abs/2104.09864
SegFormerhttps://huggingface.co/docs/transformers/model_doc/segformer
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformershttps://arxiv.org/abs/2105.15203
SEWhttps://huggingface.co/docs/transformers/model_doc/sew
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognitionhttps://arxiv.org/abs/2109.06870
SEW-Dhttps://huggingface.co/docs/transformers/model_doc/sew_d
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognitionhttps://arxiv.org/abs/2109.06870
SpeechToTextTransformerhttps://huggingface.co/docs/transformers/model_doc/speech_to_text
fairseq S2T: Fast Speech-to-Text Modeling with fairseqhttps://arxiv.org/abs/2010.05171
SpeechToTextTransformer2https://huggingface.co/docs/transformers/model_doc/speech_to_text_2
Large-Scale Self- and Semi-Supervised Learning for Speech Translationhttps://arxiv.org/abs/2104.06678
Splinterhttps://huggingface.co/docs/transformers/model_doc/splinter
Few-Shot Question Answering by Pretraining Span Selectionhttps://arxiv.org/abs/2101.00438
SqueezeBERThttps://huggingface.co/docs/transformers/model_doc/squeezebert
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?https://arxiv.org/abs/2006.11316
Swin Transformerhttps://huggingface.co/docs/transformers/model_doc/swin
Swin Transformer: Hierarchical Vision Transformer using Shifted Windowshttps://arxiv.org/abs/2103.14030
Swin Transformer V2https://huggingface.co/docs/transformers/model_doc/swinv2
Swin Transformer V2: Scaling Up Capacity and Resolutionhttps://arxiv.org/abs/2111.09883
SwitchTransformershttps://huggingface.co/docs/transformers/main/model_doc/switch_transformers
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsityhttps://arxiv.org/abs/2101.03961
T5https://huggingface.co/docs/transformers/model_doc/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformerhttps://arxiv.org/abs/1910.10683
T5v1.1https://huggingface.co/docs/transformers/model_doc/t5v1.1
google-research/text-to-text-transfer-transformerhttps://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511
Table Transformerhttps://huggingface.co/docs/transformers/model_doc/table-transformer
PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documentshttps://arxiv.org/abs/2110.00061
TAPAShttps://huggingface.co/docs/transformers/model_doc/tapas
TAPAS: Weakly Supervised Table Parsing via Pre-traininghttps://arxiv.org/abs/2004.02349
TAPEXhttps://huggingface.co/docs/transformers/model_doc/tapex
TAPEX: Table Pre-training via Learning a Neural SQL Executorhttps://arxiv.org/abs/2107.07653
Time Series Transformerhttps://huggingface.co/docs/transformers/model_doc/time_series_transformer
Trajectory Transformerhttps://huggingface.co/docs/transformers/model_doc/trajectory_transformers
Offline Reinforcement Learning as One Big Sequence Modeling Problemhttps://arxiv.org/abs/2106.02039
Transformer-XLhttps://huggingface.co/docs/transformers/model_doc/transfo-xl
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contexthttps://arxiv.org/abs/1901.02860
TrOCRhttps://huggingface.co/docs/transformers/model_doc/trocr
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Modelshttps://arxiv.org/abs/2109.10282
UL2https://huggingface.co/docs/transformers/model_doc/ul2
Unifying Language Learning Paradigmshttps://arxiv.org/abs/2205.05131v1
UniSpeechhttps://huggingface.co/docs/transformers/model_doc/unispeech
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Datahttps://arxiv.org/abs/2101.07597
UniSpeechSathttps://huggingface.co/docs/transformers/model_doc/unispeech-sat
UNISPEECH-SAT: UNIVERSAL SPEECH REPRESENTATION LEARNING WITH SPEAKER AWARE PRE-TRAININGhttps://arxiv.org/abs/2110.05752
VANhttps://huggingface.co/docs/transformers/model_doc/van
Visual Attention Networkhttps://arxiv.org/abs/2202.09741
VideoMAEhttps://huggingface.co/docs/transformers/model_doc/videomae
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Traininghttps://arxiv.org/abs/2203.12602
ViLThttps://huggingface.co/docs/transformers/model_doc/vilt
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervisionhttps://arxiv.org/abs/2102.03334
Vision Transformer (ViT)https://huggingface.co/docs/transformers/model_doc/vit
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalehttps://arxiv.org/abs/2010.11929
VisualBERThttps://huggingface.co/docs/transformers/model_doc/visual_bert
VisualBERT: A Simple and Performant Baseline for Vision and Languagehttps://arxiv.org/pdf/1908.03557
ViTMAEhttps://huggingface.co/docs/transformers/model_doc/vit_mae
Masked Autoencoders Are Scalable Vision Learnershttps://arxiv.org/abs/2111.06377
ViTMSNhttps://huggingface.co/docs/transformers/model_doc/vit_msn
Masked Siamese Networks for Label-Efficient Learninghttps://arxiv.org/abs/2204.07141
Wav2Vec2https://huggingface.co/docs/transformers/model_doc/wav2vec2
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationshttps://arxiv.org/abs/2006.11477
Wav2Vec2-Conformerhttps://huggingface.co/docs/transformers/model_doc/wav2vec2-conformer
FAIRSEQ S2T: Fast Speech-to-Text Modeling with FAIRSEQhttps://arxiv.org/abs/2010.05171
Wav2Vec2Phonemehttps://huggingface.co/docs/transformers/model_doc/wav2vec2_phoneme
Simple and Effective Zero-shot Cross-lingual Phoneme Recognitionhttps://arxiv.org/abs/2109.11680
WavLMhttps://huggingface.co/docs/transformers/model_doc/wavlm
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processinghttps://arxiv.org/abs/2110.13900
Whisperhttps://huggingface.co/docs/transformers/model_doc/whisper
Robust Speech Recognition via Large-Scale Weak Supervisionhttps://cdn.openai.com/papers/whisper.pdf
X-CLIPhttps://huggingface.co/docs/transformers/model_doc/xclip
Expanding Language-Image Pretrained Models for General Video Recognitionhttps://arxiv.org/abs/2208.02816
XGLMhttps://huggingface.co/docs/transformers/model_doc/xglm
Few-shot Learning with Multilingual Language Modelshttps://arxiv.org/abs/2112.10668
XLMhttps://huggingface.co/docs/transformers/model_doc/xlm
Cross-lingual Language Model Pretraininghttps://arxiv.org/abs/1901.07291
XLM-ProphetNethttps://huggingface.co/docs/transformers/model_doc/xlm-prophetnet
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-traininghttps://arxiv.org/abs/2001.04063
XLM-RoBERTahttps://huggingface.co/docs/transformers/model_doc/xlm-roberta
Unsupervised Cross-lingual Representation Learning at Scalehttps://arxiv.org/abs/1911.02116
XLM-RoBERTa-XLhttps://huggingface.co/docs/transformers/model_doc/xlm-roberta-xl
Larger-Scale Transformers for Multilingual Masked Language Modelinghttps://arxiv.org/abs/2105.00572
XLNethttps://huggingface.co/docs/transformers/model_doc/xlnet
​XLNet: Generalized Autoregressive Pretraining for Language Understandinghttps://arxiv.org/abs/1906.08237
XLS-Rhttps://huggingface.co/docs/transformers/model_doc/xls_r
XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scalehttps://arxiv.org/abs/2111.09296
XLSR-Wav2Vec2https://huggingface.co/docs/transformers/model_doc/xlsr_wav2vec2
Unsupervised Cross-Lingual Representation Learning For Speech Recognitionhttps://arxiv.org/abs/2006.13979
YOLOShttps://huggingface.co/docs/transformers/model_doc/yolos
You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detectionhttps://arxiv.org/abs/2106.00666
YOSOhttps://huggingface.co/docs/transformers/model_doc/yoso
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Samplinghttps://arxiv.org/abs/2111.09714
templateshttps://patch-diff.githubusercontent.com/echallenge/transformers/blob/main/templates
contributing guidelineshttps://patch-diff.githubusercontent.com/echallenge/transformers/blob/main/CONTRIBUTING.md
this tablehttps://huggingface.co/docs/transformers/index#supported-frameworks
documentationhttps://github.com/huggingface/transformers/tree/main/examples
https://patch-diff.githubusercontent.com/echallenge/transformers#learn-more
Documentationhttps://huggingface.co/docs/transformers/
Task summaryhttps://huggingface.co/docs/transformers/task_summary
Preprocessing tutorialhttps://huggingface.co/docs/transformers/preprocessing
Training and fine-tuninghttps://huggingface.co/docs/transformers/training
Quick tour: Fine-tuning/usage scriptshttps://github.com/huggingface/transformers/tree/main/examples
Model sharing and uploadinghttps://huggingface.co/docs/transformers/model_sharing
Migrationhttps://huggingface.co/docs/transformers/migration
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paperhttps://www.aclweb.org/anthology/2020.emnlp-demos.6/
huggingface.co/transformershttps://huggingface.co/transformers
Readme https://patch-diff.githubusercontent.com/echallenge/transformers#readme-ov-file
Apache-2.0 license https://patch-diff.githubusercontent.com/echallenge/transformers#Apache-2.0-1-ov-file
Code of conduct https://patch-diff.githubusercontent.com/echallenge/transformers#coc-ov-file
Contributing https://patch-diff.githubusercontent.com/echallenge/transformers#contributing-ov-file
Please reload this pagehttps://patch-diff.githubusercontent.com/echallenge/transformers
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