[tune](deps): Bump transformers from 4.9.1 to 4.13.0 in /python/requirements/tune #84

dependabot · 2021-12-11T08:06:48Z

Bumps transformers from 4.9.1 to 4.13.0.

Release notes

v4.13.0: Perceiver, ImageGPT, mLUKE, Vision-Text dual encoders, QDQBert, new documentation frontend

New Model additions

Perceiver

Eight new models are released as part of the Perceiver implementation: PerceiverModel, PerceiverForMaskedLM, PerceiverForSequenceClassification, PerceiverForImageClassificationLearned, PerceiverForImageClassificationFourier, PerceiverForImageClassificationConvProcessing, PerceiverForOpticalFlow, PerceiverForMultimodalAutoencoding, in PyTorch.

The Perceiver IO model was proposed in Perceiver IO: A General Architecture for Structured Inputs & Outputs by Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira.

Add Perceiver IO by @NielsRogge in huggingface/transformers#14487

Compatible checkpoints can be found on the hub: https://huggingface.co/models?other=perceiver

mLUKE

The mLUKE tokenizer is added. The tokenizer can be used for the multilingual variant of LUKE.

The mLUKE model was proposed in mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Models by Ryokan Ri, Ikuya Yamada, and Yoshimasa Tsuruoka. It's a multilingual extension of the LUKE model trained on the basis of XLM-RoBERTa.

Add mLUKE by @Ryou0634 in huggingface/transformers#14640

Compatible checkpoints can be found on the hub: https://huggingface.co/models?other=luke

ImageGPT

Three new models are released as part of the ImageGPT integration: ImageGPTModel, ImageGPTForCausalImageModeling, ImageGPTForImageClassification, in PyTorch.

The ImageGPT model was proposed in Generative Pretraining from Pixels by Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever. ImageGPT (iGPT) is a GPT-2-like model trained to predict the next pixel value, allowing for both unconditional and conditional image generation.

Add ImageGPT by @NielsRogge in huggingface/transformers#14240

Compatible checkpoints can be found on the hub: https://huggingface.co/models?other=imagegpt

QDQBert

Eight new models are released as part of the QDQBert implementation: QDQBertModel, QDQBertLMHeadModel, QDQBertForMaskedLM, QDQBertForSequenceClassification, QDQBertForNextSentencePrediction, QDQBertForMultipleChoice, QDQBertForTokenClassification, QDQBertForQuestionAnswering, in PyTorch.

The QDQBERT model can be referenced in Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation by Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev and Paulius Micikevicius.

Add QDQBert model and quantization examples of SQUAD task by @shangz-ai in huggingface/transformers#14066

Semantic Segmentation models

... (truncated)

Commits

4da3a69 Release: v4.13.0
60be4bf Fix typo in toctree (#14704)
da7aabf add str hub token to repository when provided else fallback to default (#14682)
7375758 Fix tests (#14703)
68e53e6 Add a job to test doc building (for realsies this time) (#14662)
e980012 Add kenlm dep to missing tests
ee6674d Fix doc examples: name '...' is not defined (#14687)
e621932 Make MLuke tokenizer tests slow (#14690)
13186d7 Move pyctcdecode (#14686)
d104dd4 [trainer] support UserDict inputs (torch-nightly) (#14688)
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Bumps [transformers](https://github.com/huggingface/transformers) from 4.9.1 to 4.13.0. - [Release notes](https://github.com/huggingface/transformers/releases) - [Commits](huggingface/transformers@v4.9.1...v4.13.0) --- updated-dependencies: - dependency-name: transformers dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com>

dependabot · 2021-12-15T17:54:14Z