Add new model RoFormer (use rotary position embedding ) (#11684)
* add roformer * Update docs/source/model_doc/roformer.rst Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update docs/source/model_doc/roformer.rst Co-authored-by: Suraj Patil <surajp815@gmail.com> * update * add TFRoFormerSinusoidalPositionalEmbedding and fix TFMarianSinusoidalPositionalEmbedding * update docs * make style and make quality * roback * unchanged * rm copies from , this is a error in TFMarianSinusoidalPositionalEmbedding * update Copyright year * move # Add modeling imports here to the correct position * max_position_embeddings can be set to 1536 * # Copied from transformers.models.bert.modeling_bert.BertOutput with Bert->RoFormer * # Copied from transformers.models.bert.modeling_bert.BertLayer.__init__ with Bert->RoFormer * update tokenization_roformer * make style * add staticmethod apply_rotary_position_embeddings * add TF staticmethod apply_rotary_position_embeddings * update torch apply_rotary_position_embeddings * fix tf apply_rotary_position_embeddings error * make style * add pytorch RoFormerSelfAttentionRotaryPositionEmbeddingTest * add TF rotary_position_embeddings test * update test_modeling_rofomer * Update docs/source/model_doc/roformer.rst Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/__init__.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/__init__.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/__init__.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/__init__.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/roformer/convert_roformer_original_tf_checkpoint_to_pytorch.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/roformer/modeling_roformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/roformer/modeling_roformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/roformer/modeling_tf_roformer.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * refact roformer tokenizer * add RoFormerTokenizerFast * add RoFormerTokenizationTest * add require_jieba * update Copyright * update tokenizer & add copy from * add option rotary_value * use rust jieba * use rjieba * use rust jieba * fix test_alignement_methods * slice normalized_string is too slow * add config.embedding_size when embedding_size!=hidden_size * fix pickle tokenizer * Update docs/source/model_doc/roformer.rst Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * make style and make quality Co-authored-by: Suraj Patil <surajp815@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
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@@ -243,6 +243,7 @@ Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.
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1. **[ProphetNet](https://huggingface.co/transformers/model_doc/prophetnet.html)** (from Microsoft Research) released with the paper [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://arxiv.org/abs/2001.04063) by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.
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1. **[Reformer](https://huggingface.co/transformers/model_doc/reformer.html)** (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. **[RoBERTa](https://huggingface.co/transformers/model_doc/roberta.html)** (from Facebook), released together with the paper 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](https://huggingface.co/transformers/model_doc/roformer.html)** (from ZhuiyiTechnology), released together with the paper a [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://arxiv.org/pdf/2104.09864v1.pdf) by Jianlin Su and Yu Lu and Shengfeng Pan and Bo Wen and Yunfeng Liu.
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1. **[SpeechToTextTransformer](https://huggingface.co/transformers/model_doc/speech_to_text.html)** (from Facebook), released together 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, Dmytro Okhonko, Juan Pino.
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1. **[SqueezeBert](https://huggingface.co/transformers/model_doc/squeezebert.html)** released with the paper [SqueezeBERT: What can computer vision teach NLP about efficient neural networks?](https://arxiv.org/abs/2006.11316) by Forrest N. Iandola, Albert E. Shaw, Ravi Krishna, and Kurt W. Keutzer.
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1. **[T5](https://huggingface.co/transformers/model_doc/t5.html)** (from Google AI) released with the paper [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://arxiv.org/abs/1910.10683) 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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