* allow unused parameter passthrough when chunking in asr pipelines
* format code
* format
* run fixup
* update tests
* update parameters to pipline in test
* updates parametrs in tests
* change spelling in gitignore
* revert .gitignore to main
* add git ignore of devcontainer folder
* assert asr output follows expected inference output type
* run fixup
* Remove .devcontainer from .gitignore
* remove compliance check
Starting from version 2.4 PyTorch introduces a stricter check for the objects which
can be loaded with torch.load(). Starting from version 2.6 loading with weights_only=True
requires allowlisting of such objects.
This commit adds allowlist of some numpy objects used to load model checkpoints.
Usage is restricted by context manager. User can still additionally call
torch.serialization.add_safe_globals() to add other objects into the safe globals list.
Accelerate library also stepped into same problem and addressed it with PR-3036.
Fixes: #34631
See: https://github.com/pytorch/pytorch/pull/137602
See: https://pytorch.org/docs/stable/notes/serialization.html#torch.serialization.add_safe_globals
See: https://github.com/huggingface/accelerate/pull/3036
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
* CI Skip EETQ tests while package is broken
EETQ tries to import the shard_checkpoint function from transformers but
the function has been removed. Therefore, trying to use EETQ currently
results in an import error. This fix results in EETQ tests being skipped
if there is an import error.
The issue has been reported to EETQ:
https://github.com/NetEase-FuXi/EETQ/issues/34
* Raise helpful error when trying to use eetq
* Forget to raise the error in else clause
* skip nested deepspeed.zero.Init call
* make fixup
* solve conflict
* solve conflict
* put back local
* use context mangers instead of local thread
* Skip recursive calls to deepspeed.zero.Init
* Skip recursive calls to deepspeed.zero.Init
* back to old notebooks
* make style
* add tensor processing system to separate logic for models
* format refactoring
* small fix
* make some methods private
* move custom methods to processors
* refactor tensor processing
* format fix
* Add Nemotron GGUF Loading Support
* fix the Nemotron architecture assignation
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Do not load for meta device
* Make some minor improvements
* Add test
* Update tests/utils/test_modeling_utils.py
Update test parameters
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Make the test simpler
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Added image-text-to-text pipeline to task guide
* Update docs/source/en/tasks/image_text_to_text.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/image_text_to_text.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/image_text_to_text.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/image_text_to_text.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Merge codeblocks
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add deformable detr image processor fast
* add fast processor to doc
* fix copies
* nit docstring
* Add tests gpu/cpu and fix docstrings
* fix docstring
* import changes from detr
* fix imports
* rebase and fix
* fix input data format change in detr and rtdetr fast
* add support for openai api image_url input
* change continue to elif
* Explicitely add support for OpenAI/TGI chat format
* rewrite content to transformers chat format and add tests
* Add support for typing of image type in chat templates
* add base64 to possible image types
* refactor nesting
* Fix post process function called in the instance segmentation example of mask2former
* fix description and additional notes for post_process_instance_segmentation of maskformers
* remove white space in maskformers post_process_instance_segmentation doc
* change image.size[::-1] to height and width for clarity in segmentation examples
* add Cambricon MLUs support
* fix mlu device rng state
* up for quality check
* up mlu to support fp16
* fix mlu device dependency error
* fix mlu device dependency error
* enable mlu device for bf16
* fix mlu device memory tracker
* Cambricon support SDPA and flash_attn
* MLU devices : Checks if `mlu` is available via an `cndev-based` check which won't trigger the drivers and leave mlu
