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@dependabot dependabot bot commented on behalf of github Sep 4, 2021

Bumps transformers from 4.8.1 to 4.10.0.

Release notes

Sourced from transformers's releases.

v4.10.0: LayoutLM-v2, LayoutXLM, BEiT

LayoutLM-v2 and LayoutXLM

Four new models are released as part of the LatourLM-v2 implementation: LayoutLMv2ForSequenceClassification, LayoutLMv2Model, LayoutLMv2ForTokenClassification and LayoutLMv2ForQuestionAnswering, in PyTorch.

The LayoutLMV2 model was proposed in LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding by Yang Xu, Yiheng Xu, Tengchao Lv, Lei Cui, Furu Wei, Guoxin Wang, Yijuan Lu, Dinei Florencio, Cha Zhang, Wanxiang Che, Min Zhang, Lidong Zhou. LayoutLMV2 improves LayoutLM to obtain state-of-the-art results across several document image understanding benchmarks:

Compatible checkpoints can be found on the Hub: https://huggingface.co/models?filter=layoutlmv2

BEiT

Three new models are released as part of the BEiT implementation: BeitModel, BeitForMaskedImageModeling, and BeitForImageClassification, in PyTorch.

The BEiT model was proposed in BEiT: BERT Pre-Training of Image Transformers by Hangbo Bao, Li Dong and Furu Wei. Inspired by BERT, BEiT is the first paper that makes self-supervised pre-training of Vision Transformers (ViTs) outperform supervised pre-training. Rather than pre-training the model to predict the class of an image (as done in the original ViT paper), BEiT models are pre-trained to predict visual tokens from the codebook of OpenAI’s DALL-E model given masked patches.

Compatible checkpoints can be found on the Hub: https://huggingface.co/models?filter=beit

Speech improvements

The Wav2Vec2 and HuBERT models now have a sequence classification head available.

DeBERTa in TensorFlow (@​kamalkraj)

The DeBERTa and DeBERTa-v2 models have been converted from PyTorch to TensorFlow.

Flax model additions

EncoderDecoder, DistilBERT, and ALBERT, now have support in Flax!

TensorFlow examples

A new example has been added in TensorFlow: multiple choice! Data collators have become framework agnostic and can now work for both TensorFlow and NumPy on top of PyTorch.

... (truncated)

Commits
  • 39cb6f5 Adjust documentation index
  • 2a60ede Revert "Correct wrong function signatures on the docs website (#13198)"
  • d12bbe4 Release: v4.10.0
  • 642e193 [GitHub Runner] Fix flax runner (#13357)
  • c76de10 Add generate kwargs to Seq2SeqTrainingArguments (#13339)
  • 702f4a4 Fixed CLM model still using MODEL_FOR_MASKED_LM_MAPPING (#13002)
  • aa08a34 [Flax tests] NVIDIA-SMI failure should continue
  • 854260c TF/Numpy variants for all DataCollator classes (#13105)
  • 74b3344 Clean up test file
  • ef8d6f2 Set missing seq_length variable when using inputs_embeds with ALBERT & Remove...
  • Additional commits viewable in compare view

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@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Sep 4, 2021
Bumps [transformers](https://github.com/huggingface/transformers) from 4.8.1 to 4.10.0.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.8.1...v4.10.0)

---
updated-dependencies:
- dependency-name: transformers
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot force-pushed the dependabot/pip/python/requirements/tune/transformers-4.10.0 branch from d3a669c to fee3033 Compare September 7, 2021 16:10
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dependabot bot commented on behalf of github Sep 11, 2021

Superseded by #59.

@dependabot dependabot bot closed this Sep 11, 2021
@dependabot dependabot bot deleted the dependabot/pip/python/requirements/tune/transformers-4.10.0 branch September 11, 2021 07:05
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