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MSN (Masked Siamese Networks) for ViT (#18815)

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* feat: modeling and conversion scripts for msn.

* chore: change license year.

* chore: remove unneeded modules.

* feat: direct loading of state_dict from remote url.

* fix: import paths.

* add: rest of the files.

* add and fix rest of the files.

Co-authored-by: Niels <niels.rogge1@gmail.com>

* chore: formatting.

* code quality fix.

* chore: remove pooler.

* feat: add classification top.

* fix: configuration object.

* add: initial test cases (one failing).

* fix: basemodeloutput.

* add: caution on using the classification head.

* add: rest of the model related files.

* add: vit msn readme.

* fix: copied from statement.

* fix: dummy objects.

* add: ViTMSNPreTrainedModel to inits.

* fix: repo consistency.

* minor change in the model doc.

* fix: tests.

* Empty-Commit

* Update src/transformers/models/vit_msn/configuration_vit_msn.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* address PR comments.

* Update src/transformers/models/vit_msn/modeling_vit_msn.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* chore: put model in no_grad() and formatting.

Co-authored-by: Niels <niels.rogge1@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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Sayak Paul
2022-09-22 16:45:03 +05:30
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README_zh-hant.md
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@@ -371,6 +371,7 @@ conda install -c huggingface transformers
1. **[Vision Transformer (ViT)](https://huggingface.co/docs/transformers/model_doc/vit)** (from Google AI) released with the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.
1. **[VisualBERT](https://huggingface.co/docs/transformers/model_doc/visual_bert)** (from UCLA NLP) released with the paper [VisualBERT: A Simple and Performant Baseline for Vision and Language](https://arxiv.org/pdf/1908.03557) by Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang.
1. **[ViTMAE](https://huggingface.co/docs/transformers/model_doc/vit_mae)** (from Meta AI) released with the paper [Masked Autoencoders Are Scalable Vision Learners](https://arxiv.org/abs/2111.06377) by Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, Ross Girshick.
1. **[ViTMSN](https://huggingface.co/docs/transformers/main/model_doc/vit_msn)** (from Meta AI) released with the paper [Masked Siamese Networks for Label-Efficient Learning](https://arxiv.org/abs/2204.07141) by Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael Rabbat, Nicolas Ballas.
1. **[Wav2Vec2](https://huggingface.co/docs/transformers/model_doc/wav2vec2)** (from Facebook AI) released with the paper [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://arxiv.org/abs/2006.11477) by Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, Michael Auli.
1. **[Wav2Vec2-Conformer](https://huggingface.co/docs/transformers/model_doc/wav2vec2-conformer)** (from Facebook AI) released with the paper [FAIRSEQ S2T: Fast Speech-to-Text Modeling with FAIRSEQ](https://arxiv.org/abs/2010.05171) by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Sravya Popuri, Dmytro Okhonko, Juan Pino.
1. **[Wav2Vec2Phoneme](https://huggingface.co/docs/transformers/model_doc/wav2vec2_phoneme)** (from Facebook AI) released with the paper [Simple and Effective Zero-shot Cross-lingual Phoneme Recognition](https://arxiv.org/abs/2109.11680) by Qiantong Xu, Alexei Baevski, Michael Auli.