M-CTC-T Model (#16402)
* added cbs to notebooks, made copy-paste error fix in generation_utils * initial push for mctc model * mctc feature extractor done * added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly. * added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly. * passing attention, now struggling to figure out how attention masks make sense here * works when excluding attention masks. ask later how one would integrate attention maskshere * bizarre configuration error (model prefix comes first in config dict json and messes up the order) * all passing but bizzarre config dict ordering issue when to_dict * passing all major tests * feature extraction, processor, tokenizer added & tests passing * style & consistency & other logistical fixes * copy paste fix * model after feature extraction working * commiting final feature extraction results; need to fix normalization * feature extraction passing tests; probably should add tests on the specific flashlight-copied functions? * delete print ; format code a bit * fixing tests * passing major tests * fixing styles * completed tokenization test with real example; not sure if these values are entirely correct. * last test fixes from local * reverting accidentally included custom setup configs * remove load tf weights; fix config error * testing couldnt import featureextractor * fix docs * fix docs * resolving comments * style fixes * style fixes * Update to MCTCConv1dSubSampler Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * relposemb fixes * conv1d name issue; expecting config fail with paraentheses * fix config issue * fix config issue * fix config issue * change everything to MCTCT * fixing naming change errors * archive list * copyrights and docs * copyrights and docs * copyrights and docs * merge resolution * move tests, fix to changed optionaldependency structure * test directories changed * fixing tests * how to avoid tf tests? * how to avoid tf tests? * tests passing locally * allow mctctprocessor imported any env * allow mctctprocessor imported any env * fixed second round of feedback, need to fix docs * doc changes not being applied * all fixed * style fix * feedback fixes * fix copies and feature extraction style fix * Update tests/models/visual_bert/test_modeling_visual_bert.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * copy paste huggingface:main visual bert * added eof newline to visual bert; all tests are passing otherwise * fix slow tests by adding attention mask * change model id to speechbrain * make fix-copies * fix readme unwanted deletes * fixing readmes, make fix-copies * consistent M-CTC-T naming * Update src/transformers/models/mctct/__init__.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * all fixed but variable naming * adjust double quotes * fixed variable names * copyright and mr quilter * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * correct slow tests * make fix-copies * Update src/transformers/models/mctct/configuration_mctct.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/mctct/configuration_mctct.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * m-ctc-t not mctct Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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@@ -285,6 +285,7 @@ Current number of checkpoints: ** (from AllenAI) released with the paper [Longformer: The Long-Document Transformer](https://arxiv.org/abs/2004.05150) by Iz Beltagy, Matthew E. Peters, Arman Cohan.
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1. **[LUKE](https://huggingface.co/docs/transformers/model_doc/luke)** (from Studio Ousia) released with the paper [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://arxiv.org/abs/2010.01057) by Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, Yuji Matsumoto.
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1. **[LXMERT](https://huggingface.co/docs/transformers/model_doc/lxmert)** (from UNC Chapel Hill) released with the paper [LXMERT: Learning Cross-Modality Encoder Representations from Transformers for Open-Domain Question Answering](https://arxiv.org/abs/1908.07490) by Hao Tan and Mohit Bansal.
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1. **[M-CTC-T](https://huggingface.co/docs/transformers/main/model_doc/mctct)** (from Facebook) released with the paper [Pseudo-Labeling For Massively Multilingual Speech Recognition](https://arxiv.org/abs/2111.00161) by Loren Lugosch, Tatiana Likhomanenko, Gabriel Synnaeve, and Ronan Collobert.
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1. **[M2M100](https://huggingface.co/docs/transformers/model_doc/m2m_100)** (from Facebook) released with the paper [Beyond English-Centric Multilingual Machine Translation](https://arxiv.org/abs/2010.11125) by Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky, Sergey Edunov, Edouard Grave, Michael Auli, Armand Joulin.
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1. **[MarianMT](https://huggingface.co/docs/transformers/model_doc/marian)** Machine translation models trained using [OPUS](http://opus.nlpl.eu/) data by Jörg Tiedemann. The [Marian Framework](https://marian-nmt.github.io/) is being developed by the Microsoft Translator Team.
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1. **[MaskFormer](https://huggingface.co/docs/transformers/main/model_doc/maskformer)** (from Meta and UIUC) released with the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) by Bowen Cheng, Alexander G. Schwing, Alexander Kirillov.
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@@ -382,4 +383,4 @@ We now have a [paper](https://www.aclweb.org/anthology/2020.emnlp-demos.6/) you
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url = "https://www.aclweb.org/anthology/2020.emnlp-demos.6",
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pages = "38--45"
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}
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```
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```
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