* fix: clarify decoder usage in PretrainedConfig documentation
* Apply suggestions from code review
updated doc
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Mistaken use of De Morgan's law. Fixed "not (X or Y)"
to correct "not (X and Y)" check to raise a ValueError.
Added corresponding test to check "positive int or None" condition.
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* disable compile for most quants methods
* fix
* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* Update tests/quantization/bnb/test_mixed_int8.py
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* changes from joao suggestions
---------
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* fall back to eager if output_attentions
* improve relative position embeddings
* run modular on got_ocr2
* run-slow: sam
* fix run-length encoding
* fix tf processor errors
* update tf_sam
* fix compile error
* re-run tests
* Try working around the processor registration bugs
* oops
* Update error message
* Clarify error
* Docstring docstring docstring
* The extra content is indexed by config class, so let's grab some values out of there
* Commit my confusion as a TODO
* Resolve my confusion
* Cleanup and mostly revert to the original
* Better autoclass fallback
* Don't nest f-strings you lunatic
* Clearer error message
* Less getattr()
* Revert a lot of changes to try a different approach!
* Try the global registry
* Check the dynamic list as well as the transformers root
* Move the dynamic list somewhere safer
* Move the dynamic list somewhere even safer
* More import cleanup
* Simplify all the register_for_auto_class methods
* Set _auto_class in the register() methods
* Stop setting the cls attribute in register()
* Restore specifying the model class for Model derivatives only
* Fix accidentally taking the .__class__ of a class
* Revert register_for_auto_class changes
* Fix get_possibly_dynamic_module
* No more ALL_CUSTOM_CLASSES
* Fix up get_possibly_dynamic_module as well
* Revert unnecessary formatting changes
* Trigger tests
* Set best_model_checkpoint only when ckpt exists.
Rather than set it explicitly without checking if the checkpoint directory even exists as before, now we moved the setting logic inside of _save_checkpoint and are only setting it if it exists.
* Added best_global_step to TrainerState.
* Added tests for best_model_checkpoint.
* Fixed hard-coded values in test to prevent fail.
* Added helper func and removed hard-coded best_step.
* Added side effect patch generator for _eval.
* Added evaluate side effect func.
* Removed erroneous patching.
* Fixed minor bug.
* Applied Ruff.
* Fixed Ruff problem in make style.
* Used Trainer.set_initial_training_values.
* add support for fast image processors in add-new-model-like
* fix header not found add-fast-image-processor-cli
* Encourage adding fast image processor
* nit
* start improve doc
* update docs
* make requested modifs
Corrects the type annotation to match actual usage. The variable was typed as
Dict[str, Dict[str, Callable]] but is actually used as Dict[str, Callable]
where keys are attention mechanism names and values are the corresponding
attention functions directly. This change makes the type annotation consistent
with how the dictionary is used in the codebase.
* fix wandb hp search unable to resume from sweep_id
* format styles
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Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* refactor siglip2 fast image processor, add unused_kwargs in base fast image processor
* nits
* change unused_kwargs default to None
* update siglip2 fast image proc
* Don't accidentally mutate the base_model_tp_plan
* Co-authored by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Trigger tests
* Marking grad accum test as slow
* Add a flaky decorator
* Add a flaky decorator
* Use cyril's codeblock
* Don't copy() when it's None
* Use cyril's new codeblock
* make fixup
