* Updated Albert model Card
* Update docs/source/en/model_doc/albert.md
added the quotes in <hfoption id="Pipeline">
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* Update docs/source/en/model_doc/albert.md
updated checkpoints
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* Update docs/source/en/model_doc/albert.md
changed !Tips description
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* Update docs/source/en/model_doc/albert.md
updated text
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* Update docs/source/en/model_doc/albert.md
updated transformer-cli implementation
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* Update docs/source/en/model_doc/albert.md
changed text
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* Update docs/source/en/model_doc/albert.md
removed repeated description
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* Update albert.md
removed lines
* Update albert.md
updated pipeline code
* Update albert.md
updated auto model code, removed quantization as model size is not large, removed the attention visualizer part
* Update docs/source/en/model_doc/albert.md
updated notes
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* Update albert.md
reduced a repeating point in notes
* Update docs/source/en/model_doc/albert.md
updated transformer-CLI
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* Update docs/source/en/model_doc/albert.md
removed extra notes
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* adding model and conversion scripts
* add imports to test vjepa conversion
* fix imports and make conversion work
* fix computation for short side
* replace attention with library attention function
* cleanup more attention classes
* remove config overrides
* add test cases, fix some of the failing ones
* fix the model outputs
* fix outputs of the model per review
* fix too big model test case
* fix styling __init__.py
* fix initialization test
* remove all asserts per review
* update sorting unsorting logic as per feedback
* remove is_video per review
* remove another is_video segment
* remove unwanted stuff
* small fixes
* add docstrings for the model
* revert adding vjepa2 config here
* update styling
* add config docstrings (wip)
* fix dpr issue
* removed test failing issues
* update styles
* merge predictor configs into main config
* remove processing code, add video processor
* remove permute which is not necessary now
* fix styles
* updated vjepa2 to be in video_processing_auto
* update comment for preprocessing
* test integration test and fix the outputs
* update test values, change test to look at repeated frames for a given image
* add a simple video processing test
* refactoring pixel_values_videos and upload ckpts to original
* fix torch_fx test cases
* remove unused config
* add all config docstrings
* add more integration tests
* add basic doc
* revert unwanted styling changes
* working make fixup
* Fix model_type in config
* Add ForVideoClassification model
* update attention implementation to fit new hf standards
* fix the preprocessing logic, ensure it matches the original model
* remove use_rope logic, cleanup
* fix docstrings
* Further cleanup, update doc
* Fix model prefix
* fix get_vision_features
* VJEPA2Embeddings style refactor
* nit, style comment
* change modules default values
* Only `str` activation in config
* GradientCheckpointingLayer
* fixup
* fix conversion script
* Remove return_dict
* remove None return typehint
* Refactor VJEPA2Layer, remove use_SiLU
* Fix fx tests
* dpr -> drop_path_rates
* move *ModelOutput on top
* format docs bit
* update docs
* update docs
* update doc example
* remove prune_heads from model
* remove unused config params
* refactor embed signature
* Add vjepa to docs
* Fix config docstring
* attention head
* update defaults
* Update docs/source/en/model_doc/vjepa2.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/vjepa2.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Fix import
* Min refactoring
* Update HUB_SOURCE and HUB_REPO in conversion script
* Add missing headers
* VJEPA -> V-JEPA in docs
* Add image to doc
* fix style
* fix init weights
* change checkpoint name in modeling tests
* Initial cls head setup
* remove rop attention from head (not needed)
* remove swigluffn - not needed
* Add siglip layer
* Replace with siglip layer
* Rename Siglip - VJEPA2
* remove unused modules
* remove siglip mlp
* nit
* remove MLP
* Refactor head cross attention
* refactor VJEPA2HeadCrossAttentionLayer
* nit renaming
* fixup
* remove commented code
* Add cls head params to config
* depth from config
* move pooler + classifier to the model
* Update for cls model signature
* move layers, rename a bit
* fix docs
* update weights init
* remove typehint for init
* add to auto-mapping
* enable tests
* Add conversion script
* fixup
* add to docs
* fix docs
* nit
* refactor for mapping
* clean
* Add integration test
* Fixing multi gpu test
* update not-split-modules
* update video cls test tolerance
* Increase test_inference_image tolerance
* Update no-split modules for multi gpu
* Apply suggestions from code review
* fixing multi-gpu
* fix docstring
* Add cls snippet to docs
* Update checkpoint
* Refactor DBRX tests to use CausalLMModelTest base classes
- Changed DbrxModelTester to inherit from CausalLMModelTester
- Changed DbrxModelTest to inherit from CausalLMModelTest
- Removed duplicate methods that are already in base classes
- Added required class attributes for model classes
- Updated pipeline_model_mapping to include feature-extraction
- Kept DBRX-specific configuration and test methods
- Disabled RoPE tests as DBRX's rotary embedding doesn't accept config parameter
This refactoring reduces code duplication and follows the pattern established
in other causal LM model tests like Gemma.
* Apply style fixes
* Trigger tests
* Refactor DBRX test
* Make sure the DBRX-specific settings are handled
* Use the attribute_map
* Fix attribute map
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Co-authored-by: openhands <openhands@all-hands.dev>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
* Simplify and update trl examples
* Remove optim_args from SFTConfig in Trainer documentation
* Update docs/source/en/trainer.md
* Apply suggestions from code review
* Update docs/source/en/trainer.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
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Co-authored-by: Quentin Gallouédec <qgallouedec@Quentins-MacBook-Pro.local>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Unbreak optimum-executorch
* use static cache if has layer_types but no sliding_window
* revert view on kv_arange
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Co-authored-by: Guang Yang <guangyang@fb.com>
* update docs with new info
* Update docs/source/en/kv_cache.md
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>
* Moved the sources to the right
* small Changes
* Some Changes to moonshine
* Added the install to pipline
* updated the monshine model card
* Update docs/source/en/model_doc/moonshine.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/moonshine.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/moonshine.md
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* Update docs/source/en/model_doc/moonshine.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/moonshine.md
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* Updated Documentation According to changes
* Fixed the model with the commits
* Update moonshine.md
* Update moshi.md
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Co-authored-by: Your Name <sohamprabhu@Sohams-MacBook-Air.local>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* remove it from all py files
* remove it from the doc
* remove it from examples
* style
* remove traces of _fast_init
* Update test_peft_integration.py
* CIs
* apply updates smolVLM (still needs workaround for chat template)
* add other models
* dump qwen omni for now, come back later
* port qwen omni from their impl
* wait, all qwens sample videos in same way!
* clean up
* make smolvlm backwards compatible and fix padding
* dix some tests
* fox smolvlm tests
* more clean up and test fixing
* delete unused arg
* fix
* address comments
* style
* fix test
* chore(pixtral): emit block attention mask when using flash attention
Since flash_attention_2 relies solely on position_ids, emitting the block attention mask avoids unnecessary memory usage and prevents OOM on large inputs.
* remove unnecessary attention_mask assignment
* Update Pegasus model card
* Fix transformers-cli command
* Update code examples to use bfloat16
* Reverted code examples to use float16
* Fix typo, update checkpoints link
* Update str formatting in code examples
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Fix typo
* Remove inaccurate badges
* Revert badge removal
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Include cache_implementation argument in quantization example
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
