[Umt5] Add google's umt5 to transformers (#24477)

* add tokenization template * update conversion script * update modeling code * update * update convert checkpoint * update modeling * revert changes on convert script * new conversion script for new format * correct position bias * cleaning a bit * Credit co authors Co-authored-by: agemagician <ahmed.elnaggar@tum.de> Co-authored-by: stefan-it <> * styling * Add docq * fix copies * add co author * Other Author * Merge branch 'main' of https://github.com/huggingface/transformers into add-umt5 * add testing * nit * Update docs/source/en/model_doc/umt5.mdx Co-authored-by: Stefan Schweter <stefan@schweter.it> * fix t5 * actual fix? * revert wrong changes * remove * update test * more fixes * revert some changes * add SPIECE_UNDERLINE * add a commone xample * upfate * fix copies * revert changes on t5 conversion script * revert bytefallback changes since there was no addition yet * fixup * fixup * ingore umt5 cutom testing folder * fix readmes * revertT5 changes * same outputs * fixup * update example * Apply suggestions from code review * style * draft addition of all new files * current update * fix attention and stuff * finish refactoring * auto config * fixup * more nits * add umt5 to init * use md format * Update README.md Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * revert changes on mt5 * revert mt4 changes * update test * more fixes * add to mapping * fix-copies * fix copies * foix retain grad * fix some tests * nits * done * Update src/transformers/models/umt5/modeling_umt5.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update docs/source/en/model_doc/umt5.md * Update src/transformers/models/umt5/__init__.py * Update docs/source/en/model_doc/umt5.md Co-authored-by: Stefan Schweter <stefan@schweter.it> * Update src/transformers/models/umt5/modeling_umt5.py * update conversion script + use google checkpoints * nits * update test and modelling * stash slow convert * update fixupd * don't change slow --------- Co-authored-by: stefan-it <> Co-authored-by: Stefan Schweter <stefan@schweter.it> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
2023-07-03 14:38:21 +09:00
parent 66ded238cd
commit 799df10aef
27 changed files with 2473 additions and 3 deletions
--- a/README_hd.md
+++ b/README_hd.md
@@ -415,6 +415,7 @@ conda install -c huggingface transformers
 1. **[TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr)** (from Microsoft) released 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.
 1. **[TVLT](https://huggingface.co/docs/transformers/model_doc/tvlt)** (from UNC Chapel Hill) released with the paper [TVLT: Textless Vision-Language Transformer](https://arxiv.org/abs/2209.14156) by Zineng Tang, Jaemin Cho, Yixin Nie, Mohit Bansal.
 1. **[UL2](https://huggingface.co/docs/transformers/model_doc/ul2)** (from Google Research) released with the paper [Unifying Language Learning Paradigms](https://arxiv.org/abs/2205.05131v1) by Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Neil Houlsby, Donald Metzler
+1. **[UMT5](https://huggingface.co/docs/transformers/main/model_doc/umt5)** (Google Research से) Hyung Won Chung, Xavier Garcia, Adam Roberts, Yi Tay, Orhan Firat, Sharan Narang, Noah Constant. द्वाराअनुसंधान पत्र [UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining](https://openreview.net/forum?id=kXwdL1cWOAi) के साथ जारी किया गया
 1. **[UniSpeech](https://huggingface.co/docs/transformers/model_doc/unispeech)** (माइक्रोसॉफ्ट रिसर्च से) साथ में दिया गया पेपर [UniSpeech: यूनिफाइड स्पीच रिप्रेजेंटेशन लर्निंग विद लेबलेड एंड अनलेबल्ड डेटा](https:/ /arxiv.org/abs/2101.07597) चेंगई वांग, यू वू, याओ कियान, केनिची कुमातानी, शुजी लियू, फुरु वेई, माइकल ज़ेंग, ज़ुएदोंग हुआंग द्वारा।
 1. **[UniSpeechSat](https://huggingface.co/docs/transformers/model_doc/unispeech-sat)** (माइक्रोसॉफ्ट रिसर्च से) कागज के साथ [UNISPEECH-SAT: यूनिवर्सल स्पीच रिप्रेजेंटेशन लर्निंग विद स्पीकर अवेयर प्री-ट्रेनिंग ](https://arxiv.org/abs/2110.05752) सानयुआन चेन, यू वू, चेंग्यी वांग, झेंगयांग चेन, झूओ चेन, शुजी लियू, जियान वू, याओ कियान, फुरु वेई, जिन्यु ली, जियांगज़ान यू द्वारा पोस्ट किया गया।
 1. **[UPerNet](https://huggingface.co/docs/transformers/model_doc/upernet)** (from Peking University) released with the paper [Unified Perceptual Parsing for Scene Understanding](https://arxiv.org/abs/1807.10221) by Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, Jian Sun.