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Title: GitHub - pituim/transformers: 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

Open Graph Title: GitHub - pituim/transformers: 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

X Title: GitHub - pituim/transformers: 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

Description: 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0. - pituim/transformers

Open Graph Description: 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0. - pituim/transformers

X Description: 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0. - pituim/transformers

Opengraph URL: https://github.com/pituim/transformers

X: @github

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https://patch-diff.githubusercontent.com/pituim/transformers#online-demos
model hubhttps://huggingface.co/models
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 Langugage 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
Write With Transformerhttps://transformer.huggingface.co
https://patch-diff.githubusercontent.com/pituim/transformers#quick-tour
this tutorialhttps://huggingface.co/transformers/task_summary.html
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/transformers/training.html
https://patch-diff.githubusercontent.com/pituim/transformers#why-should-i-use-transformers
https://patch-diff.githubusercontent.com/pituim/transformers#why-shouldnt-i-use-transformers
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exampleshttps://github.com/huggingface/transformers/tree/master/examples
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user guidehttps://packaging.python.org/guides/installing-using-pip-and-virtual-environments/
TensorFlow installation pagehttps://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available
PyTorch installation pagehttps://pytorch.org/get-started/locally/#start-locally
Flax installation pagehttps://github.com/google/flax#quick-install
install the library from sourcehttps://huggingface.co/transformers/installation.html#installing-from-source
https://patch-diff.githubusercontent.com/pituim/transformers#with-conda
https://patch-diff.githubusercontent.com/pituim/transformers#models-architectures
All the model checkpointshttps://huggingface.co/models
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https://camo.githubusercontent.com/f36a36c84f2ff8605938db0f71595cdfebb5ebc941833aeb2591205f220bc9d2/68747470733a2f2f696d672e736869656c64732e696f2f656e64706f696e743f75726c3d68747470733a2f2f68756767696e67666163652e636f2f6170692f736869656c64732f6d6f64656c7326636f6c6f723d627269676874677265656e
herehttps://huggingface.co/transformers/model_summary.html
ALBERThttps://huggingface.co/transformers/model_doc/albert.html
ALBERT: A Lite BERT for Self-supervised Learning of Language Representationshttps://arxiv.org/abs/1909.11942
BARThttps://huggingface.co/transformers/model_doc/bart.html
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensionhttps://arxiv.org/pdf/1910.13461.pdf
BARThezhttps://huggingface.co/transformers/model_doc/barthez.html
BARThez: a Skilled Pretrained French Sequence-to-Sequence Modelhttps://arxiv.org/abs/2010.12321
BERThttps://huggingface.co/transformers/model_doc/bert.html
BERT: Pre-training of Deep Bidirectional Transformers for Language Understandinghttps://arxiv.org/abs/1810.04805
BERT For Sequence Generationhttps://huggingface.co/transformers/model_doc/bertgeneration.html
Leveraging Pre-trained Checkpoints for Sequence Generation Taskshttps://arxiv.org/abs/1907.12461
Blenderbothttps://huggingface.co/transformers/model_doc/blenderbot.html
Recipes for building an open-domain chatbothttps://arxiv.org/abs/2004.13637
CamemBERThttps://huggingface.co/transformers/model_doc/camembert.html
CamemBERT: a Tasty French Language Modelhttps://arxiv.org/abs/1911.03894
CTRLhttps://huggingface.co/transformers/model_doc/ctrl.html
CTRL: A Conditional Transformer Language Model for Controllable Generationhttps://arxiv.org/abs/1909.05858
DeBERTahttps://huggingface.co/transformers/model_doc/deberta.html
DeBERTa: Decoding-enhanced BERT with Disentangled Attentionhttps://arxiv.org/abs/2006.03654
DialoGPThttps://huggingface.co/transformers/model_doc/dialogpt.html
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationhttps://arxiv.org/abs/1911.00536
DistilBERThttps://huggingface.co/transformers/model_doc/distilbert.html
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterhttps://arxiv.org/abs/1910.01108
DistilGPT2https://github.com/huggingface/transformers/tree/master/examples/distillation
DistilRoBERTahttps://github.com/huggingface/transformers/tree/master/examples/distillation
DistilmBERThttps://github.com/huggingface/transformers/tree/master/examples/distillation
DPRhttps://huggingface.co/transformers/model_doc/dpr.html
Dense Passage Retrieval for Open-Domain Question Answeringhttps://arxiv.org/abs/2004.04906
ELECTRAhttps://huggingface.co/transformers/model_doc/electra.html
ELECTRA: Pre-training text encoders as discriminators rather than generatorshttps://arxiv.org/abs/2003.10555
FlauBERThttps://huggingface.co/transformers/model_doc/flaubert.html
FlauBERT: Unsupervised Language Model Pre-training for Frenchhttps://arxiv.org/abs/1912.05372
Funnel Transformerhttps://huggingface.co/transformers/model_doc/funnel.html
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processinghttps://arxiv.org/abs/2006.03236
GPThttps://huggingface.co/transformers/model_doc/gpt.html
Improving Language Understanding by Generative Pre-Traininghttps://blog.openai.com/language-unsupervised/
GPT-2https://huggingface.co/transformers/model_doc/gpt2.html
Language Models are Unsupervised Multitask Learnershttps://blog.openai.com/better-language-models/
LayoutLMhttps://huggingface.co/transformers/model_doc/layoutlm.html
LayoutLM: Pre-training of Text and Layout for Document Image Understandinghttps://arxiv.org/abs/1912.13318
Longformerhttps://huggingface.co/transformers/model_doc/longformer.html
Longformer: The Long-Document Transformerhttps://arxiv.org/abs/2004.05150
LXMERThttps://huggingface.co/transformers/model_doc/lxmert.html
LXMERT: Learning Cross-Modality Encoder Representations from Transformers for Open-Domain Question Answeringhttps://arxiv.org/abs/1908.07490
MarianMThttps://huggingface.co/transformers/model_doc/marian.html
OPUShttp://opus.nlpl.eu/
Marian Frameworkhttps://marian-nmt.github.io/
MBarthttps://huggingface.co/transformers/model_doc/mbart.html
Multilingual Denoising Pre-training for Neural Machine Translationhttps://arxiv.org/abs/2001.08210
MPNethttps://huggingface.co/transformers/model_doc/mpnet.html
MPNet: Masked and Permuted Pre-training for Language Understandinghttps://arxiv.org/abs/2004.09297
MT5https://huggingface.co/transformers/model_doc/mt5.html
mT5: A massively multilingual pre-trained text-to-text transformerhttps://arxiv.org/abs/2010.11934
Pegasushttps://huggingface.co/transformers/model_doc/pegasus.html
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationhttps://arxiv.org/abs/1912.08777
ProphetNethttps://huggingface.co/transformers/model_doc/prophetnet.html
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-traininghttps://arxiv.org/abs/2001.04063
Reformerhttps://huggingface.co/transformers/model_doc/reformer.html
Reformer: The Efficient Transformerhttps://arxiv.org/abs/2001.04451
RoBERTahttps://huggingface.co/transformers/model_doc/roberta.html
Robustly Optimized BERT Pretraining Approachhttps://arxiv.org/abs/1907.11692
DistilmBERThttps://github.com/huggingface/transformers/tree/master/examples/distillation
SqueezeBerthttps://huggingface.co/transformers/model_doc/squeezebert.html
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?https://arxiv.org/abs/2006.11316
T5https://huggingface.co/transformers/model_doc/t5.html
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformerhttps://arxiv.org/abs/1910.10683
TAPAShttps://huggingface.co/transformers/master/model_doc/tapas.html
TAPAS: Weakly Supervised Table Parsing via Pre-traininghttps://arxiv.org/abs/2004.02349
Transformer-XLhttps://huggingface.co/transformers/model_doc/transformerxl.html
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contexthttps://arxiv.org/abs/1901.02860
XLMhttps://huggingface.co/transformers/model_doc/xlm.html
Cross-lingual Language Model Pretraininghttps://arxiv.org/abs/1901.07291
XLM-ProphetNethttps://huggingface.co/transformers/model_doc/xlmprophetnet.html
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-traininghttps://arxiv.org/abs/2001.04063
XLM-RoBERTahttps://huggingface.co/transformers/model_doc/xlmroberta.html
Unsupervised Cross-lingual Representation Learning at Scalehttps://arxiv.org/abs/1911.02116
XLNethttps://huggingface.co/transformers/model_doc/xlnet.html
​XLNet: Generalized Autoregressive Pretraining for Language Understandinghttps://arxiv.org/abs/1906.08237
templateshttps://patch-diff.githubusercontent.com/pituim/transformers/blob/master/templates
contributing guidelineshttps://patch-diff.githubusercontent.com/pituim/transformers/blob/master/CONTRIBUTING.md
this tablehttps://huggingface.co/transformers/index.html#bigtable
documentationhttps://huggingface.co/transformers/examples.html
https://patch-diff.githubusercontent.com/pituim/transformers#learn-more
Documentationhttps://huggingface.co/transformers/
Task summaryhttps://huggingface.co/transformers/task_summary.html
Preprocessing tutorialhttps://huggingface.co/transformers/preprocessing.html
Training and fine-tuninghttps://huggingface.co/transformers/training.html
Quick tour: Fine-tuning/usage scriptshttps://github.com/huggingface/transformers/tree/master/examples
Model sharing and uploadinghttps://huggingface.co/transformers/model_sharing.html
Migrationhttps://huggingface.co/transformers/migration.html
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Readme https://patch-diff.githubusercontent.com/pituim/transformers#readme-ov-file
Apache-2.0 license https://patch-diff.githubusercontent.com/pituim/transformers#Apache-2.0-1-ov-file
Code of conduct https://patch-diff.githubusercontent.com/pituim/transformers#coc-ov-file
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