Improve T5 docs (huggingface#13240)

* Remove disclaimer * First draft * Fix rebase * Improve docs some more * Add inference section * Improve example scripts section * Improve code examples of modeling files * Add docs regarding task prefix * Address @craffel's comments * Apply suggestions from @patrickvonplaten's review Co-authored-by: Patrick von Platen <[email protected]> * Add suggestions from code review * Apply @sgugger's suggestions * Fix Flax code examples * Fix index.rst Co-authored-by: Patrick von Platen <[email protected]>
jacob-crux · Sep 1, 2021 · 4766e00 · 4766e00
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diff --git a/README.md b/README.md
@@ -272,6 +272,7 @@ Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.
 1. **[Splinter](https://huggingface.co/transformers/model_doc/splinter.html)** (from Tel Aviv University), released together with the paper [Few-Shot Question Answering by Pretraining Span Selection](https://arxiv.org/abs/2101.00438) by Ori Ram, Yuval Kirstain, Jonathan Berant, Amir Globerson, Omer Levy.
 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.
 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.
+1. **[T5v1.1](https://huggingface.co/transformers/model_doc/t5v1.1.html)** (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.
 1. **[TAPAS](https://huggingface.co/transformers/model_doc/tapas.html)** (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.
 1. **[Transformer-XL](https://huggingface.co/transformers/model_doc/transformerxl.html)** (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.
 1. **[Vision Transformer (ViT)](https://huggingface.co/transformers/model_doc/vit.html)** (from Google AI) released with the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -282,35 +282,40 @@ Supported models
 62. :doc:`T5 <model_doc/t5>` (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.
-63. :doc:`TAPAS <model_doc/tapas>` (from Google AI) released with the paper `TAPAS: Weakly Supervised Table Parsing via
+63. :doc:`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.
+64. :doc:`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.
-64. :doc:`Transformer-XL <model_doc/transformerxl>` (from Google/CMU) released with the paper `Transformer-XL:
+65. :doc:`Transformer-XL <model_doc/transformerxl>` (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.
-65. :doc:`Vision Transformer (ViT) <model_doc/vit>` (from Google AI) released with the paper `An Image is Worth 16x16
+66. :doc:`Vision Transformer (ViT) <model_doc/vit>` (from Google AI) released with the paper `An Image is Worth 16x16
     Words: Transformers for Image Recognition at Scale <https://arxiv.org/abs/2010.11929>`__ by Alexey Dosovitskiy,
     Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias
     Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.
-66. :doc:`VisualBERT <model_doc/visual_bert>` (from UCLA NLP) released with the paper `VisualBERT: A Simple and
+67. :doc:`VisualBERT <model_doc/visual_bert>` (from UCLA NLP) released with the paper `VisualBERT: A Simple and
     Performant Baseline for Vision and Language <https://arxiv.org/pdf/1908.03557>`__ by Liunian Harold Li, Mark
     Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang.
-67. :doc:`Wav2Vec2 <model_doc/wav2vec2>` (from Facebook AI) released with the paper `wav2vec 2.0: A Framework for
+68. :doc:`Wav2Vec2 <model_doc/wav2vec2>` (from Facebook AI) released with the paper `wav2vec 2.0: A Framework for
     Self-Supervised Learning of Speech Representations <https://arxiv.org/abs/2006.11477>`__ by Alexei Baevski, Henry
     Zhou, Abdelrahman Mohamed, Michael Auli.
-68. :doc:`XLM <model_doc/xlm>` (from Facebook) released together with the paper `Cross-lingual Language Model
+69. :doc:`XLM <model_doc/xlm>` (from Facebook) released together with the paper `Cross-lingual Language Model
     Pretraining <https://arxiv.org/abs/1901.07291>`__ by Guillaume Lample and Alexis Conneau.
-69. :doc:`XLM-ProphetNet <model_doc/xlmprophetnet>` (from Microsoft Research) released with the paper `ProphetNet:
+70. :doc:`XLM-ProphetNet <model_doc/xlmprophetnet>` (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.
-70. :doc:`XLM-RoBERTa <model_doc/xlmroberta>` (from Facebook AI), released together with the paper `Unsupervised
+71. :doc:`XLM-RoBERTa <model_doc/xlmroberta>` (from Facebook AI), released together with the paper `Unsupervised
     Cross-lingual Representation Learning at Scale <https://arxiv.org/abs/1911.02116>`__ by Alexis Conneau*, Kartikay
     Khandelwal*, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke
     Zettlemoyer and Veselin Stoyanov.
-71. :doc:`XLNet <model_doc/xlnet>` (from Google/CMU) released with the paper `XLNet: Generalized Autoregressive
+72. :doc:`XLNet <model_doc/xlnet>` (from Google/CMU) released with the paper `XLNet: Generalized Autoregressive
     Pretraining for Language Understanding <https://arxiv.org/abs/1906.08237>`__ by Zhilin Yang*, Zihang Dai*, Yiming
     Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le.
-72. :doc:`XLSR-Wav2Vec2 <model_doc/xlsr_wav2vec2>` (from Facebook AI) released with the paper `Unsupervised
+73. :doc:`XLSR-Wav2Vec2 <model_doc/xlsr_wav2vec2>` (from Facebook AI) released with the paper `Unsupervised
     Cross-Lingual Representation Learning For Speech Recognition <https://arxiv.org/abs/2006.13979>`__ by Alexis
     Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed, Michael Auli.
 
@@ -608,6 +613,7 @@ Flax), PyTorch, and/or TensorFlow.
     model_doc/splinter
     model_doc/squeezebert
     model_doc/t5
+    model_doc/t5v1.1
     model_doc/tapas
     model_doc/transformerxl
     model_doc/vit

diff --git a/docs/source/model_doc/byt5.rst b/docs/source/model_doc/byt5.rst
@@ -39,8 +39,11 @@ experiments.*
 This model was contributed by `patrickvonplaten <https://huggingface.co/patrickvonplaten>`__. The original code can be
 found `here <https://github.com/google-research/byt5>`__.
 
+ByT5's architecture is based on the T5v1.1 model, so one can refer to :doc:`T5v1.1's documentation page <t5v1.1>`. They
+only differ in how inputs should be prepared for the model, see the code examples below.
 
-ByT5's architecture is based on the T5 model, so one can refer to :doc:`T5's documentation page <t5>`.
+Since ByT5 was pre-trained unsupervisedly, there's no real advantage to using a task prefix during single-task
+fine-tuning. If you are doing multi-task fine-tuning, you should use a prefix.
 
 
 Example

diff --git a/docs/source/model_doc/mt5.rst b/docs/source/model_doc/mt5.rst
@@ -28,6 +28,23 @@ multilingual variant of T5 that was pre-trained on a new Common Crawl-based data
 the design and modified training of mT5 and demonstrate its state-of-the-art performance on many multilingual
 benchmarks. All of the code and model checkpoints*
 
+Note: mT5 was only pre-trained on `mC4 <https://huggingface.co/datasets/mc4>`__ excluding any supervised training.
+Therefore, this model has to be fine-tuned before it is useable on a downstream task, unlike the original T5 model.
+Since mT5 was pre-trained unsupervisedly, there's no real advantage to using a task prefix during single-task
+fine-tuning. If you are doing multi-task fine-tuning, you should use a prefix.
+
+Google has released the following variants:
+
+- `google/mt5-small <https://huggingface.co/google/mt5-small>`__
+
+- `google/mt5-base <https://huggingface.co/google/mt5-base>`__
+
+- `google/mt5-large <https://huggingface.co/google/mt5-large>`__
+
+- `google/mt5-xl <https://huggingface.co/google/mt5-xl>`__
+
+- `google/mt5-xxl <https://huggingface.co/google/mt5-xxl>`__.
+
 This model was contributed by `patrickvonplaten <https://huggingface.co/patrickvonplaten>`__. The original code can be
 found `here <https://github.com/google-research/multilingual-t5>`__.