GitLab

Co-authored-by: Guoming Zhang <37257613+nv-guomingz@users.noreply.github.com>

* Remove size check between attn_weights and kv_seq_len

* add unit tests

* [whisper] compile compatibility with long-form decoding

* clarify comment

* fix after rebase

* finalise

* fix bsz

* fix cache split

* remove contiguous

* style

* finish

* update doc

* prevent cuda graph trace

cache class flag

* Fixed staticmethods with self as first argument.

* Fixed staticmethods with self as first argument.

* Fixed staticmethods with self as first argument.

* Fixed staticmethods with self as first argument.

* draft

* apply changes to all relevant archs

* rerun ci - check_docstrings.py failing?

* fix docstring

* move 2D->4D mask creation to modeling file

* repo consistency

* fix the batch size = 1 case - calling contiguous is not enough

* nit

* style

* propagate to gemma/gemma-2

* prepare inputs for gemma generation

* implement test and tiny fix in gemma2

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

* fix copies

* ci pass

* fix gemma's test_compile_static_cache tests

* flacky

* retrigger ci

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

Fix error when streaming agent run to gradio with non-string tool arguments

* Fix FA2 call for Perciever layer

* [run_slow] idefics2

* [run_slow] idefics2

* [run_slow] idefics2

* Fix up

* [run_slow] idefics2

* [run_slow] idefics2

* [run_slow] idefics2

fix 💩

* enable flash-attn & static cache

* this works, not the prev

* fix for sliding window layers

* not needed anymore

fix

* Remove user-defined tokens which can be obtained through merges

* Remove debug line

* formatting

* Refactor spm slow -> fast converter

* revert unnecessary refactor

* set comprehension

* remove test files

* Use `vocab_scores`

* Always replace spiece underline with space in decode

* we no longer need token filtering

* Add save fast load slow unit test

* Remove tokenizers version check

* Remove duplicate code

* Make `<start_of_turn>` and `<end_of_turn>` special tokens

* Bias merge priority with length if score is the same

* Add unit test for merge priority

* CI

* tmp

* skip files not in the diff

* use git.Repo instead of an external subprocess

* add tiny change to confirm that the diff is working on pushed changes

* add make quality task

* more profesh main commit reference

fixes #32329 : The Torch code is correct - to get an average of 10% of the total, we want to take 50% of the remainder after we've already masked 80% with [MASK] in the previous step.

fixes to properly shard FSDP across cpu and meta for cpu_efficient_loading for prequantized 4bit (#32276)

Fixed raising of few exceptions.

* new agent plan

* plan type assertion

* style corrections

* better prompt naming

* make fixup

* doc formatting nits

* ignore non-autodocs

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

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

* make fixup

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

* tentative fix

* do the same for M4T

* fix epochs_trained as int when resuming training

* refactor

---------
Co-authored-by: teddyferdinan <teddy.ferdinan@pwr.edu.pl>

* fix gguf dequantize for gguf==0.9.1

* fix old version

* make style

Docs: fix GaLore optimizer example

Fix incorrect usage of GaLore optimizer in Transformers trainer code example.

The GaLore optimizer uses low-rank gradient updates to reduce memory usage. GaLore is quite popular and is implemented by the authors in [https://github.com/jiaweizzhao/GaLore](https://github.com/jiaweizzhao/GaLore). A few months ago GaLore was added to the HuggingFace Transformers library in https://github.com/huggingface/transformers/pull/29588.

Documentation of the Trainer module includes a few code examples of how to use GaLore. However, the `optim_targe_modules` argument to the `TrainingArguments` function is incorrect, as discussed in https://github.com/huggingface/transformers/pull/29588#issuecomment-2006289512. This pull request fixes this issue.

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

* Add stream_to_gradio method for running agent in gradio demo

* [pipeline] fix padding for 1-d tensors

* add test

* make style

* Update tests/pipelines/test_pipelines_automatic_speech_recognition.py
Co-authored-by: Kamil Akesbi <45195979+kamilakesbi@users.noreply.github.com>

* Update tests/pipelines/test_pipelines_automatic_speech_recognition.py

---------
Co-authored-by: Kamil Akesbi <45195979+kamilakesbi@users.noreply.github.com>

* fix _fix_key in PreTrainedModel

* fix _find_longest_common_sequence

* add test

* remove result.json

* nit

* update test

* mvp

* added test (a few models need fixes)

* fix a few test cases

* test nits

* harder test 😈

* revert changes in stablelm

* test with improved condition

* add todo

* tmp commit

* merged with main

* nits

* add todo

* final corrections

* add docs for generation compilation

* docs nits

* add  tip

* PR suggestions

* add more details to the compilation docs

* fix cache positions

* cache is now init in generate; update docs

* tag test as flaky

* docs

* post rebase make fixup and other nits

* remove unintended changes

* whisper (encoder-decoder) not supported

* move token default updates to ; add tests for token defaults

* push changes

* manual rebase

* chameleon doesn't support this

* fix test_static_cache_mha_mqa_gqa (broken in another PR)

* docs: dynamic is better with end-to-end compilation

Fixed a link in docs.

* fix

* bug fix

* refine

* fix

remove exceptions

Removed one wrong argument passed to convert_blip_checkpoint function call.

* Optimize t5 tokenize logic to avoid redundant calls

* fix and overwrite copies

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

* bloom dynamic cache

* bloom follows standard cache format

* no skips for bloom anymore

* use cache position when possible

* clean up

* codestyle

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

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

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

* pr comments

* isinstance fix

* address comments

* make musicgen test happy

* [run-slow] bloom

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

* replace for loop by tensor ops

* rm assert; readability