GitLab

* add: initial script to train clm fim

* fix: if training model from scratch, new tokens will be added and embeddings resized

* fix: fixed attention_mask errors when generating FIM data

* fix: file formatted using black

* add: run_fim_no_trainer.py and fixed some comments in run_fim.py

* add: added fim examples to the README.md and ran code fixup

* fix: little bug in both fim training scripts

* fix: remove comment from notebook and added a note on fim related params

* fix: minor typo in README

* add: suggested minor changes to README and run_fim.py

* add: gradient_accumulation_steps and gradient_checkpointing args

* add: improved model embedding resizing

* add: pad_to_multiple_of and attn_implementation params

* add: requested minor changes

* add: deepspeed zero compatibility

* add: resize embeddings layer with zero3 support for fim model initialization

* post merge update

* nit

* oups

feat: use `warning_advice` instead of tensorflow warning

* Fix eval thread fork bomb

* Keep eval dl persistent and prepare after so free_memory doesn't destroy it

* Add note

* Quality

[tests] use the correct `n_gpu` in `TrainerIntegrationTest::test_train_and_eval_dataloaders` for XPU (#29307)

* fix n_gpu

* fix style

fix total silence input with no_speech_threshold

fix FSDP config

* Make sliding window size inclusive in eager attention

* Fix tests

* fix stablelm dropout argument type error

* fix docs of _flash_attention_forward

* fix all docs of _flash_attention_forward

* fix docs of _flash_attention_forward in starcoder2

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Co-authored-by: oliang <oliang@tencent.com>

* use torch_device

* skip for XPU

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

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

* fix image-to-text batch incorrect output issue
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* add ci test
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* update ci test
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* add sacremoses check

* fix style

* for FlaubertTokenizer

* HerbertTokenizer fix

* add typeHint

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

* make less skipped

* make quality

* remove import

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

* left-padding test revisited

* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

Potential typo in mlx support

* 🐛 Fix vision encoder decoder positional arg

* ✅

 Add test for VisionEncoderDecoder with LayoutLMv3 encoder

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Co-authored-by: Nick DeGroot <1966472+nickthegroot@users.noreply.github.com>

* Set `inputs` as kwarg in `TextClassificationPipeline`

This change has been done to align the `TextClassificationPipeline` with the rest of the pipelines, and to be able to e.g. `pipeline(**{"inputs": "text"})` which wouldn't be possible since the `*args` were being used instead.

* Add `noqa: C409` on `tuple([inputs],)`

Even though is discouraged by the linter, the cast `tuple(list(...),)` is required here, as otherwise the original list in `inputs` will be transformed into a `tuple` and the elements 1...N will be ignored by the `Pipeline`

* Run `ruff format`

* Simplify `tuple` conversion with `(inputs,)`
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

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Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Fall back to pytorch model for now

* Fix up

Add support for loading safetensors files saved with metadata format mlx.

* flava multimodal add attn mask

* make style

* check mask is not None

Signed-off-by: Ashok Pon Kumar Sree Prakash <ashokponkumar@gmail.com>

Revert "Automatic safetensors conversion when lacking these files (#29390)"

This reverts commit a69cbf4e.

* Enable BLIP for auto VQA

* Make style

* Add VQA to BLIP pipeline tests

* Fix: Disable torch.autocast in RotaryEmbedding of Gemma and LLaMa for MPS devices

* Update src/transformers/models/gemma/modeling_gemma.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update llama ang gemma rope use cpu in mps device

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

Substantially reduce memory usage in _update_causal_mask for large batches by using .expand instead of .repeat [needs tests+sanity check] (#29413)

* try to fix gemma mem use

* fix: handle attention mask dim==2 case

* remove logits=logits.float()

* clean up + add llama

* apply formatting

* readability edit: swap order of items being multiplied

* revert change unrelated to PR

* revert black autoformat

* switch to one .to

* Accept style edits
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* added the max_matching_ngram_size parameter into the GenerationConfig, for the PromptLookupCandidateGenerator

* switched back to keyword arguments

* added PromptLookupCandidateGenerator docstring for its parameters

* ruff reformat

* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix test failure

* use item

* Fix TrainingArguments regression with torch <2.0.0 for dataloader_prefetch_factor

dataloader_prefetch_factor was added to TrainingArguments in #28498 with the default value None, but  versions of torch<2.0.0 do not accept None and will raise an error if num_workers == 0 and prefetch_factor != 2

* Add is_torch_available() check

* Use is_torch_greater_or_equal_than_2_0

add back check for dataloader_prefetch_factor

* add accelerate docs

* Apply suggestions from code review
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* Update starcoder2.md

* add correct generation

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Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* add docs on exllamav2 + AWQ

* Update docs/source/en/quantization.md

* use require_torch_gpu

* enable on XPU

* fix

* Update ko _toctree.yml

* Create ko: generation_strategies.md

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Jungnerd <46880056+jungnerd@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Jungnerd <46880056+jungnerd@users.noreply.github.com>

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Jungnerd <46880056+jungnerd@users.noreply.github.com>

* [i18n-zh] Translate add_new_pipeline.md into Chinese

* apply suggestions from Fan-Lin