GitLab

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

* add support for siglip and chinese-clip model training with contrastive-image-text example

* codebase fixups

* Revert "Add tie_weights() to LM heads and set bias in set_output_embeddings() (#28948)"

This reverts commit 725f4ad1.

* Revert "Patch to skip failing `test_save_load_low_cpu_mem_usage` tests (#29043)"

This reverts commit 4156f517.

* add add_dummy_prefix_space option to slow

* checking kwargs might be better. Should be there for all spm tokenizer IMO

* nits

* fix copies

* more copied

* nits

* add prefix space

* nit

* nits

* Update src/transformers/convert_slow_tokenizer.py

* fix inti

* revert wrong styling

* fix

* nits

* style

* updates

* make sure we use slow tokenizer for conversion instead of looking for the decoder

* support llama ast well

* update llama tokenizer fast

* nits

* nits nits nits

* update the doc

* update

* update to fix tests

* skip unrelated tailing test

* Update src/transformers/convert_slow_tokenizer.py

* add proper testing

* test decode as well

* more testing

* format

* fix llama test

* Apply suggestions from code review

* handle peft + compiled models

* add tests

* fixup

* adapt from suggestions

* clarify comment

* only compile when needed

* fix mra as well

* fix yoso as well

* update

* rempve comment

* Update src/transformers/models/deformable_detr/modeling_deformable_detr.py

* Update src/transformers/models/deformable_detr/modeling_deformable_detr.py

* opps

* Update src/transformers/models/deta/modeling_deta.py

* nit

* forgot to push the changes for 4bit ..

* trigger CI

* abstract image processor arg checks.

* fix signatures and quality

* add validate_ method to rescale-prone processors

* add more validations

* quality

* quality

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

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

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

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

* fix crop_size compatibility

* fix default mutable arg

* fix segmentation map + image arg validity

* remove segmentation check from arg validation

* fix quality

* fix missing segmap

* protect PILImageResampling type

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

* add back segmentation maps check

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

* add RMSProp to Trainer

* revert some change

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

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

Move misplaced line, improve code comment

* default to use it

* style

* Fixed nll with label_smoothing to nll

* Resolved conflict by rebase

* Fixed nll with label_smoothing to nll

* Resolved conflict by rebase

* Added label_smoothing to config file

* Fixed nits

* report grad_norm during training

* support getting grad_norm from deepspeed

* Update base.py

* Fix a typo

* generated text on A10G

* generated text in CI

* Apply suggestions from code review

add explanatory comments
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

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

output_logits option behaves like output_scores, but returns the raw, unprocessed prediction logit scores,
ie. the values before they undergo logit processing and/or warping. The latter happens by default for the
regular output scores.

It's useful to have the unprocessed logit scores in certain circumstances. For example, unprocessed logit scores
are very useful with causallm models when one wants to determine the probability of a certain answer, e.g.
when asking a question with a yes/no answer. In that case getting the next-token probabilities of both "yes" and
"no" (and/or their relative ratio) is of interest for classification. The reason for getting these _before_ logit
processing and/or warping is b/c a) that can change the probabilities or b) reject the tokens of interest / reduce
the number of tokens to just 1.

For an example use-case see paper TabLLM: Few-shot Classification of Tabular Data with Large Language Models
by Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, and David Sontag.
https://arxiv.org/abs/2210.10723



In addition:
- added dedicated unit test: tests/generation/test_utils/test_return_unprocessed_logit_scores
  which tests return of logics with output_logits=True in generation.
- set output_logits=True in all other generation unit tests, that also have output_scores=True.

Implemented @gante's and @amyeroberts review feedback
Co-authored-by: kx79wq <max.baak@ing.com>

* Add resource

* Add more resources

* Add resources

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

* Remove mention

* Remove pipeline tags

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

* change version

* nuke

* this doesn't make sense

* update some requirements.py

* revert + no main

* nits

* change cache number

* more pin

* revert

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

Fix test

The link in evaluation was missing a hyphen between post and processing. I fixed this, for English only. Someone with the ability to do a global search/replace should fix the other languages (if indeed they have this issue)/

Update test_mixed_int8.py

* add peft support for AWQ

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

* fix

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

* Add task_summary to es/_toctree.yml

* Add task_summary.md to docs/es

* Change title of task_summary.md

* Translate firsts paragraphs

* Translate middle paragraphs

* Translte the rest of the doc

* Edit firts paragraph

* Add chat support to text generation pipeline

* Better handling of single elements

* Deprecate ConversationalPipeline

* stash commit

* Add missing add_special_tokens kwarg

* Update chat templating docs to refer to TextGenerationPipeline instead of ConversationalPipeline

* Add ✨TF✨

 tests

* @require_tf

* Add type hint

* Add specific deprecation version

* Remove unnecessary do_sample

* Remove todo - the discrepancy has been resolved

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

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

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

* FIx trainer test

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

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

* Added option to set tracking URI for MLflowCallback.

* Added option to set tracking URI for MLflowCallback.

* Changed  to  in docstring.

* pass through trust_remote_code for dynamically loading unregistered tokenizers specified by config
add test

* change directories back to previous directory after test

* fix ruff check

* Add a note to that block for future in case we want to remove it later

---------
Co-authored-by: Matt <rocketknight1@gmail.com>

Update trainer.py

* fix heuristic num_assistant_tokens_schedule

* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/generation/candidate_generator.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update utils.py

check that candidate_generator.assistant_model exists since some some speculations (like ngram and PLD) don't have assistant_model attribute

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

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

* make fixup

* merge conflict

* fix docstring

* make fixup

---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* made changes for object detection models

* added support for segmentation models.

* Made changes for segmentaion models

* Changed import statements

* solving conflicts

* removed conflicts

* Resolving commits

* Removed conflicts

* Fix : Pixel_mask_value set to False

* fix max_length for inputs_embeds

* make style

* Update src/transformers/generation/utils.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Static Cache: load models with MQA or GQA (#28975)

* fix

* fix tests

* fix tests

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

* more fixes

* make style

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

* Script & Manual edition

* Update

Update utils.py