* enable optional RMS in BitLinear
* Fix naming
* Import RMS from Llama using config.*
* make fix-copies
* ran CI loop
* remove default BitNetQuantConfig values
* Fix BitNetQuantConfig to be Optional
* Fix config docstrings to match Optoinal
* Edit docstrings to match standards
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Co-authored-by: steinmetzc <codysteinmetz7@gmail.com>
Co-authored-by: codys12 <steinmetzc@dh-mgmt4.hpc.msoe.edu>
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
* Include output embedding as well with `include_embedding` flag
Summary:
att
Test Plan:
python tests/quantization/torchao_integration/test_torchao.py -k test_include_embedding
Reviewers:
Subscribers:
Tasks:
Tags:
* format
* rename include_embedding to include_input_output_embeddings
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Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
* disable deepspeed when setting up fake trainer
* Apply style fixes
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Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
* enable trainer test cases on xpu
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
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Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* mvp
* remove trust_remote_code
* generate_from_hub
* handle requirements; docs
* english
* doc PR suggestions
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* changed remote code path to generate/generate.py
* model repo has custom generate -> override base generate
* check for proper inheritance
* some doc updates (missing: tag-related docs)
* update docs to model repo
* nit
* nit
* nits
* Update src/transformers/dynamic_module_utils.py
* Apply suggestions from code review
* Update docs/source/en/generation_strategies.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* trust remote code is required
* use new import utils for requirements version parsing
* use org examples
* add tests
* Apply suggestions from code review
Co-authored-by: Manuel de Prada Corral <6536835+manueldeprada@users.noreply.github.com>
* ascii file structure; tag instructions on readme.md
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Manuel de Prada Corral <6536835+manueldeprada@users.noreply.github.com>
* enable csm test cases on XPU, all passed
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
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Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* enable finegrained_fp8 cases on XPU
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* change back to auto
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* rename per comments
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
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Signed-off-by: Yao Matrix <matrix.yao@intel.com>
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* init vilt image processor fast
* Refactor image processor tests to use loop for all processors
* Add ViltImageProcessorFast with PyTorch-based optimized image processing
* Change made automatically by make fixup command
* Change made automatically by make fix-copies command
* Fix type hints in ViltImageProcessorFast for Python compatibility
* Define constants for image resizing based on COCO dataset aspect ratio
* Add missing property initializations to ViltImageProcessorFast
* Extract resize logic into dedicated method in ViltImageProcessorFast
* Extract padding logic into dedicated method
* Implement shape-based image grouping for optimized processing in Vilt
* Update test suite to verify ViltImageProcessorFast attributes
* Move variable declarations to _preprocess method parameters
* Remove unused parameters
* Rename _resize method to resize to override existing function
* Remove whitespace
* Remove unnecessary type check and conversion for stacked_images
* Remove redundant loop and apply padding directly to stacked images
* Refactor pad function to return images and mask as tuple instead of dict
* Add tests comparing padding masks in slow and fast implementations
* Update ViltImageProcessor tests to ensure compatibility between slow and fast implementations
* Replace add_start_docstrings with auto_docstring in ViltImageProcessorFast
* Move docstrings of custom args to ViltFastImageProcessorKwargs
* Use reorder_images function for both masks and images
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Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* fix llava processor to calculate unpad size correctly
* repo consistency
* Revert "repo consistency" & "setUp in llava family"
This reverts commit 26a50af8db.
* add edge case test for padding & unpadding
* compute unpadding size from original size
* make test config explicit
* Revert "compute unpadding size from original size"
This reverts commit 752cd27ad9.
* Revert "add edge case test for padding & unpadding"
This reverts commit ccbd094d69.
* revert unpad logic
* remove irrelevant tests
* model test
* remove processor from model test
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Co-authored-by: jaycha <jaycha@ncsoft.com>
* chore(qwen2): display warning log only when sliding window attention is enabled
* Align modeling_qwen2.py and modular_qwen2.py
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Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
