Add trajectory transformer (#17141)
* Add trajectory transformer Fix model init Fix end of lines for .mdx files Add trajectory transformer model to toctree Add forward input docs Fix docs, remove prints, simplify prediction test Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Apply suggestions from code review Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Update docs, more descriptive comments Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Update readme Small comment update and add conversion script Rebase and reformat Fix copies Fix rebase, remove duplicates Fix rebase, remove duplicates * Remove tapex * Remove tapex * Remove tapex
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@@ -142,6 +142,7 @@ The library currently contains JAX, PyTorch and TensorFlow implementations, pret
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1. **[T5v1.1](model_doc/t5v1.1)** (from Google AI) released in the repository [google-research/text-to-text-transfer-transformer](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511) 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. Liu.
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1. **[TAPAS](model_doc/tapas)** (from Google AI) released with the paper [TAPAS: Weakly Supervised Table Parsing via Pre-training](https://arxiv.org/abs/2004.02349) by Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno and Julian Martin Eisenschlos.
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1. **[TAPEX](model_doc/tapex)** (from Microsoft Research) released with the paper [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou.
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1. **[Trajectory Transformer](model_doc/trajectory_transformers)** (from the University of California at Berkeley) released with the paper [Offline Reinforcement Learning as One Big Sequence Modeling Problem](https://arxiv.org/abs/2106.02039) by Michael Janner, Qiyang Li, Sergey Levine
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1. **[Transformer-XL](model_doc/transfo-xl)** (from Google/CMU) released with the paper [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://arxiv.org/abs/1901.02860) by Zihang Dai*, Zhilin Yang*, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov.
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1. **[TrOCR](model_doc/trocr)** (from Microsoft), released together with the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv.org/abs/2109.10282) by Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, Furu Wei.
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1. **[UniSpeech](model_doc/unispeech)** (from Microsoft Research) released with the paper [UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data](https://arxiv.org/abs/2101.07597) by Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang.
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@@ -259,6 +260,7 @@ Flax), PyTorch, and/or TensorFlow.
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| Swin | ❌ | ❌ | ✅ | ✅ | ❌ |
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| T5 | ✅ | ✅ | ✅ | ✅ | ✅ |
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| TAPAS | ✅ | ❌ | ✅ | ✅ | ❌ |
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| Trajectory Transformer | ❌ | ❌ | ✅ | ❌ | ❌ |
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| Transformer-XL | ✅ | ❌ | ✅ | ✅ | ❌ |
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| TrOCR | ❌ | ❌ | ✅ | ❌ | ❌ |
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| UniSpeech | ❌ | ❌ | ✅ | ❌ | ❌ |
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