GitLab

* fix EVERYTHING

* more fixes

* ⚗️⚗️ Tokenizer magic ⚗️⚗

️

* wrong value but test passes for the TODO

* update

* updat

* safe protobuf import?

* style

* non gated repo

* update

* fixup

* Update src/transformers/models/llama/tokenization_llama.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/llama/tokenization_llama.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/t5/test_tokenization_t5.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* nits

* fix t5 too

* use assert equal

* fix llama decoding

* nits on t5

* fixup

* only remove the prefix space, not other spaces

* more deconding tests and more todos

* fix CI as well

* fixup

* skip failing test on CI (its tf its ok)

* skip test_subword_regularization_tokenizer that is also crashing on the CI for TF

* update llama

* revert good fixes

* fixup

* empty

* explain why we need to encode with an additional token

* better warning?

* nits

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* remove unused module

* remove old feed_forward_proj

* fixup

* fix

* revert cahnges and update resizing of embedding layer

* use wraning

* fixup

* more styling nits

* fix all tests that overload the embedding tests

* 👀👀 remove breakpoint

* remove useless overload + overload correctly where needed

* resize lm head with new vocab size

* reverse not necessary changes

* style

* fix CIs!

* fix last CI tests, adapt bark and Marian

* fixup

* Adds `TRANSFORMERS_TEST_DEVICE`
Mirrors the same API in the diffusers library. Useful in transformers
too.

* replace backend checking with trying `torch.device`

* Adds better error message for unknown test devices

* `make style`

* adds documentation showing `TRANSFORMERS_TEST_DEVICE` usage.

Remove added back copied from statement

* Update default rescale_factor value

* Formatting

* fix

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Add documentation to dynamic module utils

* Address review comments

* [ASR Pipeline] Fix init

* refactor test

* change default kwarg setting

* only perform checks if we have to

* override init

* move pre/forward/post checks to sanitize

* Add copied from statements for image processors

* Move out rescale and normalize to base image processor

* Remove rescale and normalize from vit (post rebase)

* Update docstrings and tidy up

* PR comments

* Add input_data_format as preprocess argument

* Resolve tests and tidy up

* Remove num_channels argument

* Update doc strings -> default ints not in code formatting

* Make training args fully immutable

* Working tests, PyTorch

* In test_trainer

* during testing

* Use proper dataclass way

* Fix test

* Another one

* Fix tf

* Lingering slow

* Exception

* Clean

add __repr__

check for case where auxiliary_head is None in UperNetPreTrainedModel

* Remove softmax for EfficientNet

* Update integration test values

* Fix up

* fix nits

* fix docstring

* fix doc

* fix damp_percent

* fix doc

Bug fix - convert out side of loop

add can_generate=True to SpeechT5ForTextToSpeech

* Add missing type hints to `BigBirdForQuestionAnswering`

* Add type hints to `Blip2QFormerModel`

* Add type hints for `ConditionalDetr` family

Remove wonky logger block

fix : escape key of start_token from special characters before search end_token in token2json function of DonutProcessor  (#25472)

fix : escape key of start_token from special characters before searching for end_token

* Enable specifying input data format - overriding inferring

* Add tests

* GTPQ integration

* Add tests for gptq

* support for more quantization model

* fix style

* typo

* fix method

* Update src/transformers/modeling_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add dataclass and fix quantization_method

* fix doc

* Update tests/quantization/gptq/test_gptq.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* modify dataclass

* add gtpqconfig import

* fix typo

* fix tests

* remove dataset as req arg

* remove tokenizer import

* add offload cpu quantization test

* fix check dataset

* modify dockerfile

* protect trainer

* style

* test for config

* add more log

* overwrite torch_dtype

* draft doc

* modify quantization_config docstring

* fix class name in docstring

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* more warning

* fix 8bit kwargs tests

* peft compatibility

* remove var

* fix is_gptq_quantized

* remove is_gptq_quantized

* fix wrap

* Update src/transformers/modeling_utils.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* add exllama

* skip test

* overwrite float16

* style

* fix skip test

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix docsting formatting

* add doc

* better test

---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fully rebased solution

* 500

* [WavLM] Fix Arxiv link and authors

* make style

* strict gen config save; Add tests

* add note that the warning will be an exception in v4.34

Update pooler output

* aligned sample_beam specs with beam_search

* pull origin main

* Revert "pull origin main"

This reverts commit 06d356f1137bb52272e120a03636598c44449cf3.

* update test_utils.py

* fix format

* remove comment

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Co-authored-by: Shogo Fujita <shogo.fujita@legalontech.jp>

* update bark generation configs for more coherent parameter

* make style

* update bark hub repo