RegNet (#16188)
* base model done * make style * done * added files * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Trigger doc build * resolved conversations * resolved conversations * seer models * minor changes * minor changes * make fixup * glob variables * minor changes * fix copies * config when possibile * resolved conflicts * resolved conflicts * resolved conflicts * CI * conversion script for 10b param * fixed for 10b model * minor updates in the doc + make style * removed unused code * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * removed unused code * removed unused code * updated modeling_utils from main Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
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@@ -124,6 +124,7 @@ The library currently contains JAX, PyTorch and TensorFlow implementations, pret
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1. **[REALM](model_doc/realm.html)** (from Google Research) released with the paper [REALM: Retrieval-Augmented Language Model Pre-Training](https://arxiv.org/abs/2002.08909) by Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat and Ming-Wei Chang.
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1. **[Reformer](model_doc/reformer)** (from Google Research) released with the paper [Reformer: The Efficient Transformer](https://arxiv.org/abs/2001.04451) by Nikita Kitaev, Łukasz Kaiser, Anselm Levskaya.
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1. **[RemBERT](model_doc/rembert)** (from Google Research) released with the paper [Rethinking embedding coupling in pre-trained language models](https://arxiv.org/abs/2010.12821) by Hyung Won Chung, Thibault Févry, Henry Tsai, M. Johnson, Sebastian Ruder.
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1. **[RegNet](model_doc/regnet)** (from META Platforms) released with the paper [Designing Network Design Space](https://arxiv.org/abs/2003.13678) by Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, Piotr Dollár.
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1. **[ResNet](model_doc/resnet)** (from Microsoft Research) released with the paper [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun.
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1. **[RoBERTa](model_doc/roberta)** (from Facebook), released together with the paper [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://arxiv.org/abs/1907.11692) by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov.
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1. **[RoFormer](model_doc/roformer)** (from ZhuiyiTechnology), released together with the paper [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://arxiv.org/abs/2104.09864) by Jianlin Su and Yu Lu and Shengfeng Pan and Bo Wen and Yunfeng Liu.
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@@ -234,6 +235,7 @@ Flax), PyTorch, and/or TensorFlow.
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| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
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| Realm | ✅ | ✅ | ✅ | ❌ | ❌ |
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| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
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| RegNet | ❌ | ❌ | ✅ | ❌ | ❌ |
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| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
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| ResNet | ❌ | ❌ | ✅ | ❌ | ❌ |
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| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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