* Iterative generation using input embeds
* Add Janus model
* discard changes
* Janus imports
* Refactor config and processor
* Added Vision tower of Janus
* Import Janus Image processor
* Vision tower fixes
* Refactor code
* Added VQ Model
* Complete model integration
* temp conversion script
* processor refactor
* Adding files to facilitate pulling
* Fixes after debugging
* Skip test for these models
* Add Janus Model
* discard changes
* Janus imports
* Refactor config and processor
* Added Vision tower of Janus
* Import Janus Image processor
* Vision tower fixes
* Refactor code
* Added VQ Model
* Complete model integration
* temp conversion script
* processor refactor
* Adding files to facilitate pulling
* Fixes after debugging
* Refactor to Text config
* ✨ Added generate function
* Saving intermediate convert file. Still need to read configs from the hub and convert them to our format.
* Adding version that reads from the JSON files. Still have to tweak some parameters manually.
* relative imports
* Initial tests
* Refactor image processor
* Seemingly working version of the conversion script, will need to test further.
* Adding command message
* Fixing conflicting JanusTextConfig class
* Incorporating some of the discussed changes.
* Small fix to create dir.
* Removing system from JINJA template
* Adding draft processor tests
* style fixes
* Minor fixes and enhancement
* added generation config
* Initial tests
* Small modifications, tests are now passing.
* Small changes I noticed while reading code.
* more fixes
* Added JanusModel class
* Small merge adaptations
* Small merge adaptations
* Image processing tests passing
* More tests and fixes
* Convert script updated and refactored
* Tests and cleanup
* make style
* Postprocessing for image generation
* generate refactor
* fixes
* - Passing tests that write a part of the model to cpu (e.g. test_cpu_offload)
- Passing tests of dispatching SDPA
- Only gradient checkpointing tests are left.
* Removing temporary code
* Changes
* Writing change to modular
* Added JanusVisionModel. SDPA dispatch tests pass more robustly. Gradient checkpoint tests are next
* Gradient checkpoint tests passing
* Removing debug code
* Major generate refactor 😮💨
* Temp changes for testing
* Green quality CI
* 2 out of 4 integration tests passing
* breadcrumbs
* Usage Examples
* Regenerate modeling after merge
* dirty code
* JanusIntegrationTest are passing
* breadcrumbs
* happy CI
* fixes
* Changing template
* nits
* Text generation logits matching original codebase at 100% precision
* Remove ./tmp from git tracking
* Remove ./tmp from git tracking
* Checkpointing changes after reviewing
* Fixing code in docstrings
* CHanging comments and small bug in convert file
* Fixing bug in image_token_id for 7B version
* Removing line that was added by both of us
* Pushing changes after discussion. Only one left is to change the key mapping for convert file.
* Updating module file
* New convert file using dict. Tested that it is equivalent to the old one by:
- comparing keys in a script
- comparing checksums of the output files between version generated with the current convert script and those generated with the old script. This is a more reliable test.
* revert changes
* mistake
* consistency change for CI
* make style
* doc fixes
* more fixes
* experimenting with masking out pad token
* checkpoint
* Batched generation with multi-images working for 1B models. Will test 7B next.
* Device fix.
* Writing changes to modular, previous ones were written to modeling just for quick testing.
* Using passed processor attention mask (only in modeling for now)
* Matching performance done in the non-standard way
* Working version of batched generation. Will change how some args are passed to make it more similar to language case
* More compliant version of the code
* Removed duplicated `_prepare_4d_causal_attention_mask_with_cache_position`
* Updating modular file, making masked filling with paddings more efficient
* Slightly more efficient version
* Modifying JanusVisionModel to be a wrapper
* Fixing test to comply with new names
* Modular overhaul
* More refactoring
* - Changing JanusVisionModel back
- Changing forward pass
- Adding boi token to the comparison
* - Removing whole context model_ids
- Using inherited implementation of prepare_inputs_for_generation
* Moving the way boi token is passed to the model
* Fixing sdpa test
* Minor changes
* testing changes
* Minor fix
* - Adding postprocessing test
- checking values of generated image on integration test
* changes
* Removing pooled attention vision module, fixing convert script as a consequence
* More changes
* Fixes
* Draft after merge
* Bug fixes
* More bug fix
* Fixing docs
* Nits
* Refactor return dict
* Moving image post processing test to main processor post process
* Passing guidance_scale as kwarg
* make style
* 🔥 refactor
* make style
* Update and green CI
* Nits and tests update
* up
* Added MID block
* fix
* Dead code
* update testcase
* update
* model_id change
* init_weight changes
---------
Co-authored-by: hsilva664 <metallic-silver@hotmail.com>
* add support for fast tokenizer
* make style
* fix according to reviews
* make style
* relax slow_fast_equivalence mean diff
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
* added efficientnet image preprocessor but tests fail
* ruff checks pass
* ruff formatted
* properly pass rescale_offset through the functions
* - corrected indentation, ordering of methods
- reshape test passes when casted to float64
- equivalence test doesn't pass
* all tests now pass
- changes order of rescale, normalize acc to slow
- rescale_offset defaults to False acc to slow
- resample was causing difference in fast and slow. Changing test to bilinear resolves this difference
* ruff reformat
* F.InterpolationMode.NEAREST_EXACT gives TypeError: Object of type InterpolationMode is not JSON serializable
* fixes offset not being applied when do_rescale and do_normalization are both true
* - using nearest_exact sampling
- added tests for rescale + normalize
* resolving reviews
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* initial documentation
* rename mask to attention_mask
* smaller tests
* fixup
* fix copies
* move to time series section
* sort docs
* isort fix
* batch_size is not a configuration
* rename to TimesFMModelForPrediction
* initial script
* add check_outputs
* remove dropout_rate
* works with torch.Tensor inputs
* rename script
* fix docstrings
* fix freq when window_size is given
* add loss
* fix _quantile_loss
* formatting
* fix isort
* add weight init
* add support for sdpa and flash_attention_2
* fixes for flash_attention
* formatting
* remove flash_attention
* fix tests
* fix file name
* fix quantile loss
* added initial TimesFMModelIntegrationTests
* fix formatting
* fix import order
* fix _quantile_loss
* add doc for SDPA
* use timesfm 2.0
* bug fix in timesfm decode function.
* compare mean forecasts
* refactor type hints, use CamelCase
* consolidate decode func
* more readable code for weight conversion
* fix-copies
* simpler init
* renaem TimesFmMLP
* use T5LayerNorm
* fix tests
* use initializer_range
* TimesFmModel instead of TimesFmDecoder
* TimesFmPositionalEmbedding takes config for its init
* 2.0-500m-pytorch default configs
* use TimesFmModel
* fix formatting
* ignore TimesFmModel for testing
* fix docstring
* override generate as its not needed
* add doc strings
* fix logging
* add docstrings to output data classes
* initial copy from t5
* added config and attention layers
* add TimesFMPositionalEmbedding
* calcuate scale_factor once
* add more configs and TimesFMResidualBlock
* fix input_dims
* standardize code format with black
* remove unneeded modules
* TimesFM Model
* order of imports
* copy from Google official implementation
* remove covariate forecasting
* Adapting TimesFM to HF format
* restructing in progress
* adapted to HF convention
* timesfm test
* the model runs
* fixing unit tests
* fixing unit tests in progress
* add post_init
* do not change TimesFMOutput
* fixing unit tests
* all unit tests passed
* remove timesfm_layers
* add intermediate_size and initialize with config
* initial documentation
* rename mask to attention_mask
* smaller tests
* fixup
* fix copies
* move to time series section
* sort docs
* isort fix
* batch_size is not a configuration
* rename to TimesFMModelForPrediction
* initial script
* add check_outputs
* remove dropout_rate
* works with torch.Tensor inputs
* rename script
* fix docstrings
* fix freq when window_size is given
* add loss
* fix _quantile_loss
* formatting
* fix isort
* add weight init
* add support for sdpa and flash_attention_2
* fixes for flash_attention
* formatting
* remove flash_attention
* fix tests
* fix file name
* fix quantile loss
* added initial TimesFMModelIntegrationTests
* fix formatting
* fix import order
* fix _quantile_loss
* add doc for SDPA
* use timesfm 2.0
* bug fix in timesfm decode function.
* compare mean forecasts
* refactor type hints, use CamelCase
* consolidate decode func
* more readable code for weight conversion
* fix-copies
* simpler init
* renaem TimesFmMLP
* use T5LayerNorm
* fix tests
* use initializer_range
* TimesFmModel instead of TimesFmDecoder
* TimesFmPositionalEmbedding takes config for its init
* 2.0-500m-pytorch default configs
* use TimesFmModel
* fix formatting
* ignore TimesFmModel for testing
* fix docstring
* override generate as its not needed
* add doc strings
* fix logging
* add docstrings to output data classes
* add _CHECKPOINT_FOR_DOC
* fix comments
* Revert "fix comments"
This reverts commit 8deeb3e191.
* add _prepare_4d_attention_mask
* we do not have generative model classes
* use Cache
* return past_key_values
* modules initialized with config only
* update year
* Update docs/source/en/model_doc/timesfm.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add layer_idx to cache
* modular timesfm
* fix test
* unwrap sequential class
* fix toctree
* remove TimesFmOnnxConfig
* fix modular
* remove TimesFmStackedDecoder
* split qkv layer into individual layers
* rename projection layers
* use ALL_ATTENTION_FUNCTIONS
* is_causal is True
* rename config
* does not support flash_attn_2
* formatting
* fix typo in docsstring
* rename inputs
* add time series mapping
* Update src/transformers/models/olmo2/modeling_olmo2.py
* Update src/transformers/models/moonshine/modeling_moonshine.py
* use updated arguments
* fix class name
* add MODEL_FOR_TIME_SERIES_PREDICTION_MAPPING
* isort
* consolidate _preprocess into forward
* fix a typo
* fix a typo
* fix toc
* fix modular
* remove aaserts
* use self.config._attn_implementation
* move to _postprocess_output
* remove timesfm_get_large_negative_number
* use view unstead of multiple unsqueeze
* make helpers static methods of the Model
* use to_tuple
* use to_tuple if not return_dict
* remove unused intitialization block as its incorporated in nn.Linear
* remove unused num_key_value_groups
* use the same convention as the masking method
* update modular
* do not use unsqueeze
* use view instead of unsqueeze
* use buffer for inv_timescales
* formatting
* modular conversion
* remove unneeded intialization
* add missing docstrings
* remove cache
* use simple_eager_attention_forward
* support tp_plan
* support for flex and flash attention masks
* Revert "support for flex and flash attention masks"
This reverts commit def36c4fcf.
* fix device
* fix tests on gpu
* remove unsued large model test
* removed unneeded comments
* add example usage
* fix style
* add import
* Update docs/source/en/model_doc/timesfm.md
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
* inherit from LlamaRMSNorm
* use can_return_tuple decorator
* remvoe return_dict
* fix year
* Update docs/source/en/model_doc/timesfm.md
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
* pretrained does not inherit from GenerationMixin
* use model for integration test
---------
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: Rajat Sen <rsen91@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
* refactor docs
* add serialization
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* reorder
* add link
* change automatic to autoquant
Co-authored-by: DerekLiu35 <91234588+DerekLiu35@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* nits
* refactor
* add colab
* update
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: DerekLiu35 <91234588+DerekLiu35@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Refactor ColPali model documentation
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Include quantisation exemple + real images
* simpler image loading
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update VITS model card
* Update docs/source/en/model_doc/vits.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/vits.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/vits.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/vits.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update vits.md
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* VDR task guide
* Add to toctree
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/tasks/visual_document_retrieval.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix and enhance pipeline_webserver.md
Signed-off-by: Yao, Matrix <matrix.yao@intel.com>
* Update docs/source/en/pipeline_webserver.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/pipeline_webserver.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* use pipe
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
---------
Signed-off-by: Yao, Matrix <matrix.yao@intel.com>
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Add MLCD model
* Update codes for auto-mapping
* Add test scripts for MLCD
* Update doc for MLCD model
* Fix import error
* Fix import error
* Fix CI error for attention_outputs
* Fix code style for CI
* Fix code style for CI
* Fix code style for CI
* Fix code style for CI
* Fix code style for CI
* Fix CI error for initialization
* Fix code style for CI
* Fix code style for CI
* Reformat codes and docs for CI test
* Reformat codes and docs for CI test
* Remove unused attributes for CI test
* Fix style for CI test
* List MLCD in flash_attn doc
* Fix: typos, modulars, refactors from suggestions
* Refactoring convert_mlcd_weights_to_hf.py from suggestions
* Fix: docs conflicts
* Fix error for CI test
* Fix style for CI test
* Add integration test for MLCD
* Refactoring by class inheritance
* Fix: refactor attention interface, adjust codes
* Fix: merging conflicts
* Fix: merging conflicts
* Fix: style for CI test
* Fix: style for CI test
* Fix: set test_resize_embeddings to be False
* Fix: initializer for CI test
* Fix: conflicts, CI test, warning and refactoring
* Fix: merging conflicts
* Refactor
* Update docs
* Fix mistakes
* Remove unused args and fix multi-gpu error
* Revert position_embeddings
* Solve conflicts
* Solve conflicts
* Remove dummy
* Update _init_weights
* Update _init_weights
* Update _init_weights for CI test
* Add ImageProcessorFast to BiT processor
* propose a fast processor and add tests
* all tests pass except one
* run make
* remove useless print
* use same test as clip
* apply make
* Update src/transformers/models/bit/image_processing_bit_fast.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* Update setup.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* Update src/transformers/models/bit/image_processing_bit_fast.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* apply review comment
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* support fast image processor layoutlmv3
* make style
* add warning and update test
* make style
* Update src/transformers/models/layoutlmv3/image_processing_layoutlmv3_fast.py
* Update image_processing_auto.py
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* support flava fast image processor
* run style and quality
* update test
* update according to reviews
* make style
* update comment on BICUBIC
* make style
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* add test and fast image processor
* make style
* Update src/transformers/models/perceiver/image_processing_perceiver_fast.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* make style
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* First pass at speech granite
Add encoder / projector, rename things
* Combine into one model file with causal lm outputs for forward
* Add loss calc
* Fix config loading
Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com>
* Split new / old loading logic
* Use transformers integration for loading peft adapters
* Add generation wrapper for selective lora enablement
* Add note for qformer encoder automodel
* Guard torch/audio imports in feature extractor
* Handle granite speech autoclasses
* Handle optional deps in package structure for granite speech
* Add granite pretrained model def for init
* Add dummy objects for torch/torchaudio
* Add tests for granite speech processor
* Minor formatting fixes and refactoring
* Add options for falling back to config in forward
* Tentative model docstrings for granite speech
* Fix config type
* Remove legacy load
* Allow non-lora variants for granite speech
* Override weight tying for llm
* Use text config instead of llm config
* Add output embeddings getter to fix weight tying
* Fix relative imports
* computing the number of audio features, based on the raw audio sequence.
* collating audio inputs, and keeping the original lengths.
* asserted we have text. otherwise we can't specify the audio special token.
* assering the number of audio-symbols/audios match correctly.
running get validated_audios only when audio is present
* indentation bugfix + supporting different feature lengths when expanding audio.
* redundant, done in _get_validated_text
* adapting the tests:
- we must have text (not either audio or text)
- _get_num_audio_features takes a list of raw lengths, provided it insetad.
* Minor cleanup, remove unused import
* Add more tests for batch feature processing
* Allow setting offset in rel position embeddings
* Add config option for warning if peft is not installed w/ lora
* Port blip2 qformer code into granite speech
* Add sad test for numpy arr processing
* Allow numpy arrays / tuples in granite speech processor
* Fix config type for projector
* - pad instead of creating a zeros tensor, to keep the original dtype/device (support bfloat16)
- cast input_features to the model dtype (support bfloat16)
* merge Blip2QFormerConfig to GraniteSpeechProjectorConfig
* prevent a crash when re-saving/loading the model (line 109)
* consider additional edge cases during preprocessing.
* consider additional edge cases during preprocessing.
* add features mask for batched inference (bugfix)
* Minor refactor, remove multiaudio processor tests
* Add set input/output embeddings for granite speech
* Fix feature dim check in processor test
* Pop input features in embed test for granite speech
* Small fixes for test edge cases
Add granite speech to seq2seq causal lm mapping names
* Add small tests for granite speech model
* Fix data parallelism test
* Standardize model class names
* Fix check for copies
* Fix misaligned init check
* Skip granite speech in checkpoint check
* Use default for tie_word_embeddings in granite speech
* Fix non documentation granite speech repo issues
* Fix comments and docstring checks
* Add placeholder docs for granite speech
* Fix test naming collision
* Code formatting
* Rerun torch dummy obj regen
* Fix save pretrained for granite speech
* Import sorting
* Fix tests typo
* Remove offset hack
* Pass args through encoder config
* Remove unused prune heads from blip2
* removing einsum. replaced with explicit multiplication (relative positional encodings) and sdpa attention.
* remove Sequential from ConformerFeedForward and ConformerConvModule. + fix for sdpa attention
* remove GraniteSpeechConformerScale
* rename to hidden_states
* rename conformer layers to self.layers, remove the first linear from the list to keep the list homogenous.
* move pre-norm to the attention/feedforward blocks (avoid complex module wrapping)
* adding pre_norm into forward
* feature extractor refactoring to resemble how it's done in phi4multimodal.
* rename feature_extractor to audio_processor
* bugfix: input_feature_mask fix to get the exact number tokens.
* Fix pytest decorator in processor test
* Add (disabled) integration tests for granite speech
* Fix handling of optional feature masking
* Loosen validation in processing for vLLM compatability
* Formatting fixes
* Update init structure to mirror llama
* Make granite speech projector generic
* Update test config to reflect generic projector
* Formatting fixes
* Fix typos, add license
* Fix undefined var in input processing
* Cleanup and expose ctc encoder
* Add missing config docstrings
* Better var names, type hints, etc
* Set attn context size in init
* Add max pos emb to encoder config
* Cleanup feature extractor
* Add granite speech architecture details
* Remove granite speech qformer ref
* Add paper link, explicit calc for qkv
* Calculate padding directly in depthwise conv1d init
* Raise value error instead of asserting
* Reorder class defs (classes used at top)
* Precompute relpos distances
* Run formatting
* Pass attention distances through forward
* Apply suggestions from code review
Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com>
* Add todo for using common batch feature extraction
* Rename audios/features
* Ensure chat template may be provided to processor
* Move granite speech docs to audio models
* Add todos for input proc refactoring
* Fix import order
* Guard torch import
* Use relative imports
* Require torch backend for processor in granite speech
* Add backend guards in feature extractor
---------
Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com>
Co-authored-by: Avihu Dekel <avihu.dekel@ibm.com>
Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com>
* add classifier head to donut
* add to transformers __init__
* add to auto model
* fix typo
* add loss for image classification
* add checkpoint
* remove no needed import
* reoder import
* format
* consistency
* add test of classifier
* add doc
* try ignore
* update loss for all swin models
* fix tests and some clean up
* make one general test for each modality
* remove redundant merging of kwargs
* edge cases
* dont enforce slow when reloading
* fix gemma3 tests
* has to adapt llama 4 after rebase
* remove also from overriden tests
* should be green now
* initial draft
* make documentation simpler
* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* Update docs/source/en/quantization/selecting.md
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* turn pros and cons into tables
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add links to each quant method page
* separate calibration vs no calibration methods
* add calibration time estimates
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add changed
* Revert "add changed"
This reverts commit 0a0166a1fe.
* update with NEW MODEL class called GLM4
* update
* Update glm4.md
* Name
* style
* fix copies
* fixup test
---------
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* Updated documentation for Donut model
* Update docs/source/en/model_doc/donut.md
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* Update docs/source/en/model_doc/donut.md
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* Update docs/source/en/model_doc/donut.md
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* Update docs/source/en/model_doc/donut.md
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* Updated code suggestions
* Update docs/source/en/model_doc/donut.md
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* Updated code suggestion to Align with the AutoModel example
* Update docs/source/en/model_doc/donut.md
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* Updated notes section included code examples
* close hfoption block and indent
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update model card for jamba
* Apply the suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Apply suggestions from code review-2
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* update model page.
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update as per code review.
* Update docs/source/en/model_doc/jamba.md as per code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/jamba.md as per code review
`
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* update as per code review.
* fixes
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Improved Model card for Gemma2
* Made changes in gemma2 as suggested
* Made more changes in the doc (adding image, notes, closing hfoptions)
* minor fixes
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update Model card for gpt2
* Update link for gpt2 space
* fixes docs based on suggestions
* Add transformers-cli and quantization example for GPT-2
* Remove resources and flash attention docs and fix typos
* feat: edit falcon mamba card
* fix: edit statement on falconmamba arch
* Update docs/source/en/model_doc/falcon_mamba.md
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* Update docs/source/en/model_doc/falcon_mamba.md
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* Update docs/source/en/model_doc/falcon_mamba.md
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* fix: add right indent for tags
* fix: remove notas
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* model card for Mistral
* Update docs/source/en/model_doc/mistral.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Apply suggestions from code review
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* Update docs/source/en/model_doc/mistral.md
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* Update docs/source/en/model_doc/mistral.md
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* Update docs/source/en/model_doc/mistral.md
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* Update docs/source/en/model_doc/mistral.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* apply suggestions
* fix typo
* updated with comments
* updated with comments
* updated with comments
* remove hfoption block
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* Update OpenAI GPT model card
* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update OpenAI GPT model card: add usage examples and notes section
* Add API autodoc tags after Notes section for OpenAI GPT model
* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Added missing badges
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* Updated T5 model card with standardized format
* Updated T5 model card with standardized format, fixed typo
* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Update docs/source/en/model_doc/t5.md
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* Apply reviewer suggestions
* Update docs/source/en/model_doc/t5.md
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Updated model card for distilbert
* Updated the distilbert model card
* Updated model card for distilbert
* Updated the distilbert model card
* Addressed code review comments
* Addressed review comments
* fix pipeline
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update ELECTRA model card with new format
* Update ELECTRA model card with new format
* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* Update docs/source/en/model_doc/electra.md
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* close hfoption block
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Co-authored-by: Wun0 <f20191221@hyderabad.bits-pilani.ac.in>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Modify Model Card for ModernBERT.
* Update as per code review.
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update model card.
* Update model card.
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update code_llama.md
aims to handle https://github.com/huggingface/transformers/issues/36979#issuecomment-2758560598
sub part of https://github.com/huggingface/transformers/issues/36979
* Update docs/source/en/model_doc/code_llama.md
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* Update docs/source/en/model_doc/code_llama.md
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* Update docs/source/en/model_doc/code_llama.md
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* make changes as per code review
* chore: make the function smaller for attention mask visualizer
* chore[docs]: update code_llama.md with some more suggested changes
* Update docs/source/en/model_doc/code_llama.md
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* chore[docs] : Update code_llama.md with indentation changes
---------
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* Update Cohere model card to follow standard template
* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update cohere.md
Update code snippet for AutoModel, quantization, and transformers-cli
* Update cohere.md
* Update docs/source/en/model_doc/cohere.md
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* feat: updated model card for qwen_2.5_vl
* applied suggested change 1
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* applied suggested change 2
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* applied suggested change 3
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix: made requested changes for quantization and notes
* suggeested model card change 4
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* updated model card wiht suggested change 5
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* updated model card wiht suggested change 6
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* updated model card wiht suggested change 7
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* feat: applied requested changes
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* Update qwen2.md
* Update qwen2.md
* Update qwen2.md
* Update qwen2.md
* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* feat: updated model card for falcon
* fix:rewrite model description
* fix: add link to conversion script
* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* fix: Add suggested changes
* fix: typo in link for quantization
* Update docs/source/en/model_doc/falcon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/falcon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix: fix indent and close ticks
* fix: add indent
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update clip.md
* Update docs/source/en/model_doc/clip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/clip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/clip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Incorporated suggested changes
* Update docs/source/en/model_doc/clip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/clip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/clip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Initial commit for Qwen3
* fix and add tests for qwen3 & qwen3_moe
* rename models for tests.
* fix
* fix
* fix and add docs.
* fix model name in docs.
* simplify modular and fix configuration issues
* Fix the red CI: ruff was updated
* revert ruff, version was wrong
* fix qwen3moe.
* fix
* make sure MOE can load
* fix copies
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
* init commit
* style
* take comments into account
* add deepseekv3 modeling
* remove redundant code
* apply make style
* apply fix-copies
* make format
* add init files
* rename deepseekv3 into deepseek_v3 based on its model_type
* rename deepseekv3 into deepseek_v3 based on its model_type
* deepseek-v3 not deepseek_v3
* set model_type as deepseek_v3
* use default docs
* apply make
* fill type and docstring
* add rope_config_validation
* use custom DeepseekV3MLP
* hold code only for checkpoints congifuration; remove redundant
* revise rope yarn for DeepSeek variation
* rename DeepSeek-V3
* some refactoring
* revise load_hook to work properly; make moe func trainable; use llama instead of mixtral
* fix attention forward
* use -1 for not-changing dim when to use exapnd
* refactor DeepseekV3TopkRouter
* use reshape_for_rope instead of load_hook; revise attention forward for TP; rename q_head_dim with qk_head_dim
* register pre_hook and hook both
* make style
* use n_shared_experts
* Update src/transformers/models/deepseek_v3/configuration_deepseek_v3.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add test file
* update modeling_file according to modular file
* make style
* add mapping for DeepseekV3ForSequenceClassification
* remove aux_loss_alpha
* add deepseek_v3 for perf
* add deepseek_v3
* rename test as deepseekv3
* use tiny-deepseek-v3
* remove DeepseekV3ForSequenceClassification
* cache before padding
* remote output_router_logits
* Revert "remote output_router_logits"
This reverts commit f264f800d0.
* remove output_router_logits
* make e_score_correction_bias as buffer
* skip tests not compatible
* make style
* make e_score_correction_bias as buffer
* use rope_interleave instead of load_hook
* skip tests not compatible with MLA
* add doc for rope_interleave
* fix typo
* remove torch.no_grad for selecting topk
* fix post merge issue
* mrege with main and simplify
* nits
* final
* small fixes
* fix
* support TP better
* stash
* changes currently requires
* remove synch
* more fixes for TP
* temp fix for TP : some attention layers's FP8 scales are too small + shared is local colwise and anything is local if FP8 because weights are used
* updates to have generation work!
* push most of the changes
* reorder functions + call for contributions!
* update readme
* nits
* update
* ruff was updated on main
* merge with main and fix copies
* revert unrelated changes
* route all tokens to all experts when testing to avoid no gradient iddues
* finish fixing all tests
* fixup
* nit
* clean config
* last readme changes
* nit
* do cnit
* typo
* last nit
* one more one more
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: arthur@huggingface.co <arthur@ip-26-0-165-131.ec2.internal>
* no image
* test
* revert jax version updates
* make fixup
* update autodoc path for model_addition_debugger
* shieldgemma2
* add missing pages to toctree
* draft of model tracer visualiser
* add context manager in addition to decorator
* add debug utils to init
* move model debugging utils to dedicated file
* add documentation
* protect some imports
* format
* move and protect imports
* format
* doc: improve errors in case of broken dummy imports.
* format
* use automatic torch backend
* update doc
* fix backend
* (TEMP) move to dummies while backend wait
* update documentation
* doc
* add prompt depth anything model by modular transformer
* add prompt depth anything docs and imports
* update code style according transformers doc
* update code style: import order issue is fixed by custom_init_isort
* fix depth shape from B,1,H,W to B,H,W which is as the same as Depth Anything
* move prompt depth anything to vision models in _toctree.yml
* update backbone test; there is no need for resnet18 backbone test
* update init file & pass RUN_SLOW tests
* update len(prompt_depth) to prompt_depth.shape[0]
Co-authored-by: Joshua Lochner <admin@xenova.com>
* fix torch_int/model_doc
* fix typo
* update PromptDepthAnythingImageProcessor
* fix typo
* fix typo for prompt depth anything doc
* update promptda overview image link of huggingface repo
* fix some typos in promptda doc
* Update image processing to include pad_image, prompt depth position, and related explanations for better clarity and functionality.
* add copy disclaimer for prompt depth anything image processing
* fix some format typos in image processing and conversion scripts
* fix nn.ReLU(False) to nn.ReLU()
* rename residual layer as it's a sequential layer
* move size compute to a separate line/variable for easier debug in modular prompt depth anything
* fix modular format for prompt depth anything
* update modular prompt depth anything
* fix scale to meter and some internal funcs warp
* fix code style in image_processing_prompt_depth_anything.py
* fix issues in image_processing_prompt_depth_anything.py
* fix issues in image_processing_prompt_depth_anything.py
* fix issues in prompt depth anything
* update converting script similar to mllamma
* update testing for modeling prompt depth anything
* update testing for image_processing_prompt_depth_anything
* fix assertion in image_processing_prompt_depth_anything
* Update src/transformers/models/prompt_depth_anything/modular_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update src/transformers/models/prompt_depth_anything/modular_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update src/transformers/models/prompt_depth_anything/image_processing_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update src/transformers/models/prompt_depth_anything/image_processing_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update src/transformers/models/prompt_depth_anything/image_processing_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update docs/source/en/model_doc/prompt_depth_anything.md
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update docs/source/en/model_doc/prompt_depth_anything.md
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* update some testing
* fix testing
* fix
* add return doc for forward of prompt depth anything
* Update src/transformers/models/prompt_depth_anything/modular_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update tests/models/prompt_depth_anything/test_modeling_prompt_depth_anything.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* fix prompt depth order
* fix format for testing prompt depth anything
* fix minor issues in prompt depth anything doc
* fix format for modular prompt depth anything
* revert format for modular prompt depth anything
* revert format for modular prompt depth anything
* update format for modular prompt depth anything
* fix parallel testing errors
* fix doc for prompt depth anything
* Add header
* Fix imports
* Licence header
---------
Co-authored-by: Joshua Lochner <admin@xenova.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Disable inductor config setter by default
This is hard to debug and should be off by default
* remove default settings in autoquant too
* Add info to torchao.md about recommended settings
* satisfying Ruff format
Summary:
Test Plan:
Reviewers:
Subscribers:
Tasks:
Tags:
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Just import torch AdamW instead
* Update docs too
* Make AdamW undocumented
* make fixup
* Add a basic wrapper class
* Add it back to the docs
* Just remove AdamW entirely
* Remove some AdamW references
* Drop AdamW from the public init
* make fix-copies
* Cleanup some references
* make fixup
* Delete lots of transformers.AdamW references
* Remove extra references to adamw_hf
* 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
* Fix converter
* [Broken] Adds Gemma 3 to Hugging Face Transformers
* Consolidating Config and Processor params across impls
* Sorting out configuration parameters. Adds qk_norm before RoPE. Still not sure if RoPE is right.
* Additional plumbing for CausalLM and ConditionalGeneration variants
* incomplete draft of Orbax conversion script
* More complete checkpoint conversion
* Supporting Gemma 3 1B checkpoints
* Updating RoPE for multiple frequencies
* Adjustments to rotary embedder
* Proof of life for text-only operation
* Updating the conversion script to handle multimodal projection weights
* Fixing tet-only conversions
* Cleaner conversion script with multimodal support and a simpler processor
* Additional refatcors to the Gemma3Processor
* Simplified Processor to work over text representations
* Updated conversion script to join text and vision embeddings at converion time
* Logging for debugging
* Update src/transformers/models/gemma2/modeling_gemma2.py
Co-authored-by: Joshua Lochner <admin@xenova.com>
* Removed extraneous Config params
* Switching to fast tokenizer for checkpoint conversions
* isolating siglip for performance tetsing
* Minor changes for debugging tests against baselines
* Adding average pooling for soft tokens
* Updating processor code to enable simpler embedding interleaving for arbitrary number of images in prompts
* Updating conversion script for ShieldGemma 2 conversion compatibility
* Allow disable_compile to be provided as a kwarg
* Refresh from modular
* Updated conversion script and corrected sliding window
* Fix type mismatch in cache_position (#4)
* Fix dtype (#5)
* Fix type mismatch in cache_position
* Actually fix in the modular file
Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com>
---------
Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com>
* fixes for embedding table overflow and missing image_soft_token_mask from Gemma3Processor
* Adding 2D pooling for image embeddings
* Revert "Adding 2D pooling for image embeddings"
This reverts commit 65350cf531.
* Gemma3 average pooling changed from 1D to 2D
* Major refactor to Gemma3MultimodalInputProjection
* Updating Gemm 3 Auto* registrations
* Add option to save Gemma 3 chat template with tokenizer during weights conversion
* Removing unused imports
* Moving out-of-vocab handling from Gemma3Processor to Gemma3ForConditionalGeneration
* Removing duplicate config property
* Removing final logit softcapping and 1-indexing of position ids
* Fixing image processor config and none --> None typo
* Fixing sliding window size for 1B
* Updating image_mean and image_std in Image Processor
* Attention masking changed to lower triangular
* Moving image special tokens to conversion script
* Mirror image processor defaults from conversion script into Gemma3ProcessorKwargs
* Remove special token variables from symbol space
* Moving image soft token mask computation from Gemma3Processor to Gemma3ForConditionalGeneration
* tie lm_head and embedding weights
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* Correct tied weights in Gemma3CausalLM
* iterative bidirectional attention
* resolving merge conflicts
* Reverting to Gemma 2 HybridCache with sldiing window support and a sliding_window_pattern of 6
* Correcting RoPE scaling
* clean up first pass, dummy model geenration works
* final clean up before fixing tests
* causal lm test works, so fine
* Fix conversion
* Update src/transformers/models/gemma3/processing_gemma3.py
* model tests are happy
* processor tests are happy
* image processing tests added
* fixup
* Fix pre-processing in conversion
* Inputs merging
* Do not normalize vision embeddings
* Apply Ryan's (and team) changes to attention
* token type ids + mask
* template
* move embed scale, add rope scale, fix tests
* Add chat template to tokenizer
* Use prefix for causal model loading
* use existing code for sliding mask from gemma2
* self.embed_tokens already normalizes
* Correcting Gemma3TextConfig parameters in conversion script
* typo, modular overwrites my fixes
* enable device map for text model
* Conversion updates
* ultra nit: no einsums
* update image token
* copy deepcopy config + some docs
* add some test, still WIP
* Refactoring --include_chat_tempalte logic in converter
* Update src/transformers/models/gemma3/modular_gemma3.py
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
* Add eos tokens for instruct models
* dump so i can work on dgx
* Removing add_bos by default
* dump
* add fast im proc
* docs for PaS + fixup
* another fixup
* one more fixup
* fix tests
* Inverting prior BOS change
* ultra nit
* Reverting to Tokenizer saved with add_bos_token=True and chat template starting with BOS
* resize embeds, remove sqrt, add slow test outputs
* FA2 but quality is meh
* nit
* skip FA2, no idea what happened
* last bit for green CI
* please, green CI for docs
* T_T
* Fix for Gemma3 logits
* Support both options for system prompt
* Update src/transformers/models/gemma3/image_processing_gemma3_fast.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/gemma3.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/gemma3.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/gemma3.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/gemma3.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/gemma3.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Docs updates now that assets are live
* Style fixes
---------
Co-authored-by: Joshua Lochner <admin@xenova.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com>
Co-authored-by: Mayank Chaturvedi <imayank@google.com>
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: Raushan Turganbay <raushan.turganbay@alumni.nu.edu.kz>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
Co-authored-by: Lysandre <hi@lysand.re>
* update
* doc
* update
* Update docs/source/en/gguf.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add swanlab integration
* feat(integrate): add SwanLab as an optional experiment tracking tool in transformers
- Integrated SwanLab into the transformers library as an alternative for experiment tracking.
- Users can now log training metrics, hyperparameters, and other experiment details to SwanLab by setting `report_to="swanlab"` in the `TrainingArguments`.
- Added necessary dependencies and documentation for SwanLab integration.
* Fix the spelling error of SwanLabCallback in callback.md
* Apply suggestions from code review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Fix typo in comment
* Fix typo in comment
* Fix typos and update comments
* fix annotation
* chore: opt some comments
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: AAssets <20010618@qq.com>
Co-authored-by: ZeYi Lin <944270057@qq.com>
Co-authored-by: KAAANG <79990647+SAKURA-CAT@users.noreply.github.com>
* initial commit
* small fix
* move stuff to image processing file
* remove stuff in validate turn and fix return tensor
* remove liquid stuff
* in the process of addressing comments
* changes to get the right tokenization
* new __init__ works
* fixing defulat std and mean
* works
* small testing scipt -- to be deleted before merge
* remove redundant code
* addressing comments
* fix inits, add docs templates
* refactor processor, switch to gotocr image processor
* remove image proc from init
* refactor to working llava-style architecture
* Change AyaVisionModel to AyaVisionForConditionalGeneration
* add tests
* fixups
* update doc
* Adding logits_to_keep explicitly in ayavision forward to enable compatibility with cohere model
* better variable names + remove code paths
* Updates to aya_vision.md
* address comments
* adding copied from
* make style and remove unused projector_hidden_act from config
* sort init
* include usage of fast image proc and proc on cuda in doc
* update checkpoint iin test processor
* update checkpoint in test processor 2
* remove test_model and update docstring
* skip failing tests
---------
Co-authored-by: Saurabh Dash <saurabh@cohere.com>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
* refactor image processor slow got ocr
* add working image processor fast
* fix fast image processor, update doc
* use one big loop for processing patches
* decompose chat template docs
* add docs
* update model docs
* qwen2-5
* pixtral
* remove old chat template
* also video as list frames supported
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/chat_template_multimodal.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* remove audio for now
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Add implementation for DataCollatorForMultipleChoice based on docs.
* Add DataCollatorForMultipleChoice to import structure.
* Remove custom DataCollatorForMultipleChoice implementations from example scripts.
* Remove custom implementations of DataCollatorForMultipleChoice from docs in English, Spanish, Japanese and Korean.
* Refactor torch version of DataCollatorForMultipleChoice to be more easily understandable.
* Apply suggested changes and run make fixup.
* fix copies, style and fixup
* add missing documentation
* nits
* fix docstring
* style
* nits
* isort
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
* add RAdamScheduleFree optimizer
* revert schedulefree version to the minimum requirement
* refine is_schedulefree_available so that it can take min_version
* refine documents
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* update awq doc
* Update docs/source/en/quantization/awq.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/awq.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/awq.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/quantization/awq.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add note for inference
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* implement config and model building blocks
* refactor model architechture
* update model outputs
* update init param to include use_fov_model
* update param name in config
* fix hidden_states and attentions outputs for fov
* sort config
* complete minor todos
* update patching
* update config for encoder
* fix config
* use correct defaults in config
* update merge for compatibility with different image size
* restructure encoder for custom configuration
* make fov model compatible with custom config
* replace word "decoder" with "fusion"
* weight conversion script
* fix fov squeeze
* update conversion script (without test)
* upload ruff image processing
* create fast image processing
* use torch interpolation for image processing
* complete post_process_depth_estimation
* config: fix imports and sort args
* apply inference in weight conversion
* use mllama script instead for weight conversion
* clean weight conversion script
* add depth-pro status in other files
* fill docstring in config
* formatting
* more formatting
* formatting with ruff
* formatting with style
* fix copied classes
* add examples; update weight convert script
* fix using check_table.py and isort
* fix config docstring
* add depth pro to sdpa docs
* undo unintentional changes in configuration_gemma.py
* minor fixes
* test image processing
* fixes and tests
* more fixes
* use output states from image_encoder instead
* Revert "use output states from image_encoder instead"
This reverts commit 2408ec54e4.
* make embeddings dynamic
* reshape output hidden states and attentions as part of computation graph
* fix ruff formating
* fix docstring failure
* use num_fov_head_layers in tests
* update doc
* check consistency with config
* ruff formatting
* update test case
* fix ruff formatting
* add tests for fov
* use interpolation in postprocess
* run and fix slow tests locally
* use scaled_images_features for image and fov encoder
* return fused_hidden_states in fusion stage
* fix example
* fix ruff
* fix copyright license for all files
* add __all__ for each file
* minor fixes
- fix download spell
- add push_to_hub option
- fix Optional type hinting
- apply single loop for DepthProImageProcessor.preprocess
* return list in post_process_depth_estimation
* minor fixes
- capitalize start of docstring
- use ignore copy
- fix examples
- move docstring templates and custom output classes to top
- remove "-> None" typehinting from __init__
- type hinting for forward passes
- fix docstrings for custom output classes
* fix "ruff check"
* update upsample and projection
* major changes: (image size and merge optimization)
- add support for images of any size
- optimize merge operation
- remove image_size from config
- use full names instead of B, C, H, W
- remove interpolation from fusion stage
- add interpolation after merge
- move validations to config
- update integration test
- add type hints for functions
* fix push_to_hub option in weights conversion
* remove image_size in weights conversion
* major changes in the architecture
- remove all DepthProViT modules and support different backbones using the AutoModel API
- set default use_fov_model to False
- validate parameters in configuration
- update interpolate function: use "nearest" for faster computation
- update reshape_feature function: remove all special tokens, possible from different backbones
- update merge function: use padding from config instead of merge_out_size
- remove patch_to_batch and batch_to_patch conversions for now
- calculate out_size dynamically in the encoder
- leave head_mask calculation to the backbone
- fix bugs with merge
- add more comments
- update tests
* placeholder for unused config attributes
* improve docs amid review
* minor change in docs
* further optimize merge
* fix formatting
* remove unused patch/batch convertion functions
* use original F.interpolate
* improve function naming
* minor chages
- use torch_int instead of int
- use proper for newly initialized tensors
- use user provided return_dict for patch_encoder
- use if-else block instead in self.use_fov_model
* rearchitect upsample block for improved modularity
* update upsample keys in weight conversion
* improve padding in merge_patches
* use double-loop for merge
* update comments
* create feature_extractor, reduce some forward code
* introduce config.use_mask_token in dinov2
* minor fixes
* minor fixes for onnx
* update __init__ to latest format
* remove DepthProConfig.to_dict()
* major changes in backbone
* update config in weight conversion
* formatting
* converted model is fp32
* improve naming and docs for feature_extractor->reconstruct_feature_maps
* minor fixes; amid review
* create intermediate vars in func call
* use torch.testing.assert_close
* use ModuleList instead of Sequential and ModuleDict
* update docs
* include fov in integraiton tests
* update docs
* improve initialization of convolution layers
* fix unused fov keys
* update tests
* ruff format
* fix test, amid kaimming initialization
* add depthpro to toctree
* add residual layer to _no_split_modules
* architecture rework
* Update src/transformers/models/depth_pro/image_processing_depth_pro.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Update src/transformers/models/depth_pro/image_processing_depth_pro_fast.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* update docs
* improve merge_patches
* use flatten with fov_output
* ruff formatting
* update resources section in docs
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* fix typo "final_kernal_size"
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* fix output typehint for DepthProDepthEstimator
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* residual operation in 2 steps
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* use image_size instead of global patch_size in interpolation
* replace all Sequential with ModuleList
* update fov
* update heads
* fix and update conversion script for heads
* ruff formatting
* remove float32 conversion
* use "Fov" instead of "FOV" in class names
* use "Fov" instead of "FOV" in config docs
* remove prune_heads
* update fusion stage
* use device in examples
* update processor
* ruff fixes
* add do_rescale in image_processor_dict
* skip test: test_fast_is_faster_than_slow
* ruff formatting
* DepthProImageProcessorFast in other files
* revert antialias removal
* add antialias in BaseImageProcessorFast
* Revert "revert antialias removal"
This reverts commit 5caa0bd8f9.
* Revert "add antialias in BaseImageProcessorFast"
This reverts commit 3ae1134780.
* update processor for grouping and antialias
* try test_fast_is_faster_than_slow without "skip" or "flanky"
* update checkpoint
* update checkpoint
* use @is_flanky for processor test
* update checkpoint to "apple/DepthPro-hf"
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* change cuda to DEVICE
* Update docs/source/en/llm_tutorial.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add init and base image processing functions
* add add_fast_image_processor to transformers-cli
* add working fast image processor clip
* add fast image processor to doc, working tests
* remove "to be implemented" SigLip
* fix unprotected import
* fix unprotected vision import
* update ViTImageProcessorFast
* increase threshold slow fast ewuivalence
* add fast img blip
* add fast class in tests with cli
* improve cli
* add fast image processor convnext
* add LlavaPatchingMixin and fast image processor for llava_next and llava_onevision
* add device kwarg to ImagesKwargs for fast processing on cuda
* cleanup
* fix unprotected import
* group images by sizes and add batch processing
* Add batch equivalence tests, skip when center_crop is used
* cleanup
* update init and cli
* fix-copies
* refactor convnext, cleanup base
* fix
* remove patching mixins, add piped torchvision transforms for ViT
* fix unbatched processing
* fix f strings
* protect imports
* change llava onevision to class transforms (test)
* fix convnext
* improve formatting (following Pavel review)
* fix handling device arg
* improve cli
* fix
* fix inits
* Add distinction between preprocess and _preprocess, and support for arbitrary kwargs through valid_extra_kwargs
* uniformize qwen2_vl fast
* fix docstrings
* add add fast image processor llava
* remove min_pixels max_pixels from accepted size
* nit
* nit
* refactor fast image processors docstrings
* cleanup and remove fast class transforms
* update add fast image processor transformers cli
* cleanup docstring
* uniformize pixtral fast and make _process_image explicit
* fix prepare image structure llava next/onevision
* Use typed kwargs instead of explicit args
* nit fix import Unpack
* clearly separate pops and gets in base preprocess. Use explicit typed kwargs
* make qwen2_vl preprocess arguments hashable
* initial commit
* encoder+decoder layer changes WIP
* architecture checks
* working version of detection + segmentation
* fix modeling outputs
* fix return dict + output att/hs
* found the position embedding masking bug
* pre-training version
* added iamge processors
* typo in init.py
* iterupdate set to false
* fixed num_labels in class_output linear layer bias init
* multihead attention shape fixes
* test improvements
* test update
* dab-detr model_doc update
* dab-detr model_doc update2
* test fix:test_retain_grad_hidden_states_attentions
* config file clean and renaming variables
* config file clean and renaming variables fix
* updated convert_to_hf file
* small fixes
* style and qulity checks
* return_dict fix
* Merge branch main into add_dab_detr
* small comment fix
* skip test_inputs_embeds test
* image processor updates + image processor test updates
* check copies test fix update
* updates for check_copies.py test
* updates for check_copies.py test2
* tied weights fix
* fixed image processing tests and fixed shared weights issues
* added numpy nd array option to get_Expected_values method in test_image_processing_dab_detr.py
* delete prints from test file
* SafeTensor modification to solve HF Trainer issue
* removing the safetensor modifications
* make fix copies and hf uplaod has been added.
* fixed index.md
* fixed repo consistency
* styel fix and dabdetrimageprocessor docstring update
* requested modifications after the first review
* Update src/transformers/models/dab_detr/image_processing_dab_detr.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* repo consistency has been fixed
* update copied NestedTensor function after main merge
* Update src/transformers/models/dab_detr/modeling_dab_detr.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* temp commit
* temp commit2
* temp commit 3
* unit tests are fixed
* fixed repo consistency
* updated expected_boxes varible values based on related notebook results in DABDETRIntegrationTests file.
* temporarialy config modifications and repo consistency fixes
* Put dilation parameter back to config
* pattern embeddings have been added to the rename_keys method
* add dilation comment to config + add as an exception in check_config_attributes SPECIAL CASES
* delete FeatureExtractor part from docs.md
* requested modifications in modeling_dab_detr.py
* [run_slow] dab_detr
* deleted last segmentation code part, updated conversion script and changed the hf path in test files
* temp commit of requested modifications
* temp commit of requested modifications 2
* updated config file, resolved codepaths and refactored conversion script
* updated decodelayer block types and refactored conversion script
* style and quality update
* small modifications based on the request
* attentions are refactored
* removed loss functions from modeling file, added loss function to lossutils, tried to move the MLP layer generation to config but it failed
* deleted imageprocessor
* fixed conversion script + quality and style
* fixed config_att
* [run_slow] dab_detr
* changing model path in conversion file and in test file
* fix Decoder variable naming
* testing the old loss function
* switched back to the new loss function and testing with the odl attention functions
* switched back to the new last good result modeling file
* moved back to the version when I asked the review
* missing new line at the end of the file
* old version test
* turn back to newest mdoel versino but change image processor
* style fix
* style fix after merge main
* [run_slow] dab_detr
* [run_slow] dab_detr
* added device and type for head bias data part
* [run_slow] dab_detr
* fixed model head bias data fill
* changed test_inference_object_detection_head assertTrues to torch test assert_close
* fixes part 1
* quality update
* self.bbox_embed in decoder has been restored
* changed Assert true torch closeall methods to torch testing assertclose
* modelcard markdown file has been updated
* deleted intemediate list from decoder module
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* layernorm_decay_fix
* W293 fix
* ruff format fix
* black format
* ruff format
* erase last layer
* add test_get_parameter_names_rmsnorm
* rmsnorm fix
* First commit
* Finish model implementation
* First commit
* Finish model implementation
* Register zamba2
* generated modeling and configuration
* generated modeling and configuration
* added hybrid cache
* fix attention_mask in mamba
* dropped unused loras
* fix flash2
* config docstrings
* fix config and fwd pass
* make fixup fixes
* text_modeling_zamba2
* small fixes
* make fixup fixes
* Fix modular model converter
* added inheritances in modular, renamed zamba cache
* modular rebase
* new modular conversion
* fix generated modeling file
* fixed import for Zamba2RMSNormGated
* modular file cleanup
* make fixup and model tests
* dropped inheritance for Zamba2PreTrainedModel
* make fixup and unit tests
* Add inheritance of rope from GemmaRotaryEmbedding
* moved rope to model init
* drop del self.self_attn and del self.feed_forward
* fix tests
* renamed lora -> adapter
* rewrote adapter implementation
* fixed tests
* Fix torch_forward in mamba2 layer
* Fix torch_forward in mamba2 layer
* Fix torch_forward in mamba2 layer
* Dropped adapter in-place sum
* removed rope from attention init
* updated rope
* created get_layers method
* make fixup fix
* make fixup fixes
* make fixup fixes
* update to new attention standard
* update to new attention standard
* make fixup fixes
* minor fixes
* cache_position
* removed cache_position postion_ids use_cache
* remove config from modular
* removed config from modular (2)
* import apply_rotary_pos_emb from llama
* fixed rope_kwargs
* Instantiate cache in Zamba2Model
* fix cache
* fix @slow decorator
* small fix in modular file
* Update docs/source/en/model_doc/zamba2.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* several minor fixes
* inherit mamba2decoder fwd and drop position_ids in mamba
* removed docstrings from modular
* reinstate zamba2 attention decoder fwd
* use regex for tied keys
* Revert "use regex for tied keys"
This reverts commit 9007a522b1.
* use regex for tied keys
* add cpu to slow forward tests
* dropped config.use_shared_mlp_adapter
* Update docs/source/en/model_doc/zamba2.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* re-convert from modular
---------
Co-authored-by: root <root@node-2.us-southcentral1-a.compute.internal>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* إضافة الترجمة العربية: masked_language_modeling.md
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/tasks/masked_language_modeling.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update _toctree.yml
* Update _toctree.yml
* Add language_modeling.md
* Add Sequence_classifiation.md
* Update _toctree.yml
---------
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* adding blog post to model doc
* Update docs/source/en/model_doc/timm_wrapper.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* review suggestions
* review suggestions
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Initial commit with template code generated by transformers-cli
* Multiple additions to SuperGlue implementation :
- Added the SuperGlueConfig
- Added the SuperGlueModel and its implementation
- Added basic weight conversion script
- Added new ImageMatchingOutput dataclass
* Few changes for SuperGlue
* Multiple changes :
- Added keypoint detection config to SuperGlueConfig
- Completed convert_superglue_to_pytorch and succesfully run inference
* Reverted unintentional change
* Multiple changes :
- Added SuperGlue to a bunch of places
- Divided SuperGlue into SuperGlueForImageMatching and SuperGlueModel
- Added testing images
* Moved things in init files
* Added docs (to be finished depending on the final implementation)
* Added necessary imports and some doc
* Removed unnecessary import
* Fixed make fix-copies bug and ran it
* Deleted SuperGlueModel
Fixed convert script
* Added SuperGlueImageProcessor
* Changed SuperGlue to support batching pairs of images and modified ImageMatchingOutput in consequences
* Changed convert_superglue_to_hf.py script to experiment different ways of reading an image and seeing its impact on performances
* Added initial tests for SuperGlueImageProcessor
* Added AutoModelForImageMatching in missing places and tests
* Fixed keypoint_detector_output instructions
* Fix style
* Adapted to latest main changes
* Added integration test
* Fixed bugs to pass tests
* Added keypoints returned by keypoint detector in the output of SuperGlue
* Added doc to SuperGlue
* SuperGlue returning all attention and hidden states for a fixed number of keypoints
* Make style
* Changed SuperGlueImageProcessor tests
* Revert "SuperGlue returning all attention and hidden states for a fixed number of keypoints"
Changed tests accordingly
This reverts commit 5b3b669c
* Added back hidden_states and attentions masked outputs with tests
* Renamed ImageMatching occurences into KeypointMatching
* Changed SuperGlueImageProcessor to raise error when batch_size is not even
* Added docs and clarity to hidden state and attention grouping function
* Fixed some code and done refactoring
* Fixed typo in SuperPoint output doc
* Fixed some of the formatting and variable naming problems
* Removed useless function call
* Removed AutoModelForKeypointMatching
* Fixed SuperGlueImageProcessor to only accept paris of images
* Added more fixes to SuperGlueImageProcessor
* Simplified the batching of attention and hidden states
* Simplified stack functions
* Moved attention instructions into class
* Removed unused do_batch_norm argument
* Moved weight initialization to the proper place
* Replaced deepcopy for instantiation
* Fixed small bug
* Changed from stevenbucaille to magic-leap repo
* Renamed London Bridge images to Tower Bridge
* Fixed formatting
* Renamed remaining "london" to "tower"
* Apply suggestions from code review
Small changes in the docs
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Added AutoModelForKeypointMatching
* Changed images used in example
* Several changes to image_processing_superglue and style
* Fixed resample type hint
* Changed SuperGlueImageProcessor and added test case for list of 2 images
* Changed list_of_tuples implementation
* Fix in dummy objects
* Added normalize_keypoint, log_sinkhorn_iterations and log_optimal_transport docstring
* Added missing docstring
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Moved forward block at bottom
* Added docstring to forward method
* Added docstring to match_image_pair method
* Changed test_model_common_attributes to test_model_get_set_embeddings test method signature
* Removed AutoModelForKeypointMatching
* Removed image fixtures and added load_dataset
* Added padding of images in SuperGlueImageProcessor
* Cleaned up convert_superglue_to_hf script
* Added missing docs and fixed unused argument
* Fixed SuperGlueImageProcessor tests
* Transposed all hidden states from SuperGlue to reflect the standard (..., seq_len, feature_dim) shape
* Added SuperGlueForKeypointMatching back to modeling_auto
* Fixed image processor padding test
* Changed SuperGlue docs
* changes:
- Abstraction to batch, concat and stack of inconsistent tensors
- Changed conv1d's to linears to match standard attention implementations
- Renamed all tensors to be tensor0 and not tensor_0 and be consistent
- Changed match image pair to run keypoint detection on all image first, create batching tensors and then filling these tensors matches after matches
- Various changes in docs, etc
* Changes to SuperGlueImageProcessor:
- Reworked the input image pairs checking function and added tests accordingly
- Added Copied from statements
- Added do_grayscale tag (also for SuperPointImageProcessor)
- Misc changes for better code
* Formatting changes
* Reverted conv1d to linear conversion because of numerical differences
* fix: changed some code to be more straightforward (e.g. filtering keypoints) and converted plot from opencv to matplotlib
* fix: removed unnecessary test
* chore: removed commented code and added back hidden states transpositions
* chore: changed from "inconsistent" to "ragged" function names as suggested
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* docs: applied suggestions
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* docs: updated to display matched output
* chore: applied suggestion for check_image_pairs_input function
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* chore: changed check_image_pairs_input function name to validate_and_format_image_pairs and used validate_preprocess_arguments function
* tests: simplified tests for image input format and shapes
* feat: converted SuperGlue's use of Conv1d with kernel_size of 1 with Linear layers. Changed tests and conversion script accordingly
* feat: several changes to address comments
Conversion script:
- Reverted fuse batchnorm to linear conversion
- Changed all 'nn.Module' to respective SuperGlue models
- Changed conversion script to use regex mapping and match other recent scripts
Modeling SuperGlue:
- Added batching with mask and padding to attention
- Removed unnecessary concat, stack and batch ragged pairs functions
- Reverted batchnorm layer
- Renamed query, key, value and merge layers into q, k, v, out proj
- Removed Union of different Module into nn.Module in _init_weights method typehint
- Changed several method's signature to combine image0 and image1 inputs with appropriate doc changes
- Updated SuperGlue's doc with torch.no_grad()
Updated test to reflect changes in SuperGlue model
* refactor: changed validate_and_format_image_pairs function with clarity
* refactor: changed from one SuperGlueMLP class to a list of SuperGlueMLP class
* fix: fixed forgotten init weight change from last commit
* fix: fixed rebase mistake
* fix: removed leftover commented code
* fix: added typehint and changed some of arguments default values
* fix: fixed attribute default values for SuperGlueConfig
* feat: added SuperGlueImageProcessor post process keypoint matching method with tests
* fix: fixed SuperGlue attention and hidden state tuples aggregation
* chore: fixed mask optionality and reordered tensor reshapes to be cleaner
* chore: fixed docs and error message returned in validate_and_format_image_pairs function
* fix: fixed returned keypoints to be the ones that SuperPoint returns
* fix: fixed check on number of image sizes for post process compared to the pairs in outputs of SuperGlue
* fix: fixed check on number of image sizes for post process compared to the pairs in outputs of SuperGlue (bis)
* fix: Changed SuperGlueMultiLayerPerceptron instantiation to avoid if statement
* fix: Changed convert_superglue_to_hf script to reflect latest SuperGlue changes and got rid of nn.Modules
* WIP: implement Attention from an existing class (like BERT)
* docs: Changed docs to include more appealing matching plot
* WIP: Implement Attention
* chore: minor typehint change
* chore: changed convert superglue script by removing all classes and apply conv to linear conversion in state dict + rearrange keys to comply with changes in model's layers organisation
* Revert "Fixed typo in SuperPoint output doc"
This reverts commit 2120390e82.
* chore: added comments in SuperGlueImageProcessor
* chore: changed SuperGlue organization HF repo to magic-leap-community
* [run-slow] refactor: small change in layer instantiation
* [run-slow] chore: replaced remaining stevenbucaille org to magic-leap-community
* [run-slow] chore: make style
* chore: update image matching fixture dataset HF repository
* [run-slow] superglue
* tests: overwriting test_batching_equivalence
* [run-slow] superglue
* tests: changed test to cope with value changing depending on cuda version
* [run-slow] superglue
* tests: changed matching_threshold value
* [run-slow] superglue
* [run-slow] superglue
* tests: changed tests for integration
* [run-slow] superglue
* fix: Changed tensor view and permutations to match original implementation results
* fix: updated convert script and integration test to include last change in model
* fix: increase tolerance for CUDA variances
* Apply suggestions from code review
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* [run-slow] superglue
* chore: removed blank whitespaces
* [run-slow] superglue
* Revert SuperPoint image processor accident changes
* [run-slow] superglue
* refactor: reverted copy from BERT class
* tests: lower the tolerance in integration tests for SuperGlue
* [run-slow] superglue
* chore: set do_grayscale to False in SuperPoint and SuperGlue image processors
* [run-slow] superglue
* fix: fixed imports in SuperGlue files
* chore: changed do_grayscale SuperGlueImageProcessing default value to True
* docs: added typehint to post_process_keypoint_matching method in SuperGlueImageProcessor
* fix: set matching_threshold default value to 0.0 instead of 0.2
* feat: added matching_threshold to post_process_keypoint_matching method
* docs: update superglue.md to include matching_threshold parameter
* docs: updated SuperGlueConfig docstring for matching_threshold default value
* refactor: removed unnecessary parameters in SuperGlueConfig
* fix: changed from matching_threshold to threshold
* fix: re-revert changes to make SuperGlue attention classes copies of BERT
* [run-slow] superglue
* fix: added missing device argument in post_processing method
* [run-slow] superglue
* fix: add matches different from -1 to compute valid matches in post_process_keypoint_matching (and docstring)
* fix: add device to image_sizes tensor instantiation
* tests: added checks on do_grayscale test
* chore: reordered and added Optional typehint to KeypointMatchingOutput
* LightGluePR suggestions:
- use `post_process_keypoint_matching` as default docs example
- add `post_process_keypoint_matching` in autodoc
- add `SuperPointConfig` import under TYPE_CHECKING condition
- format SuperGlueConfig docstring
- add device in convert_superglue_to_hf
- Fix typo
- Fix KeypointMatchingOutput docstring
- Removed unnecessary line
- Added missing SuperGlueConfig in __init__ methods
* LightGluePR suggestions:
- use batching to get keypoint detection
* refactor: processing images done in 1 for loop instead of 4
* fix: use @ instead of torch.einsum for scores computation
* style: added #fmt skip to long tensor values
* refactor: rollbacked validate_and_format_image_pairs valid and invalid case to more simple ones
* refactor: prepare_imgs
* refactor: simplified `validate_and_format_image_pairs`
* docs: fixed doc
---------
Co-authored-by: steven <steven.bucaillle@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Steven Bucaille <steven.bucaille@buawei.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Convert more checkpoints
* Update docs, convert huge variant
* Update model name
* Update src/transformers/models/vitpose/modeling_vitpose.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Remove print statements
* Update docs/source/en/model_doc/vitpose.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Link to collection
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Add input ids to model output
* Add text preprocessing for processor
* Fix snippet
* Add test for equivalence
* Add type checking guard
* Fixing typehint
* Fix test for added `input_ids` in output
* Add deprecations and "text_labels" to output
* Adjust tests
* Fix test
* Update code examples
* Minor docs and code improvement
* Remove one-liner functions and rename class to CamelCase
* Update docstring
* Fixup
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
Enhanced installation section with troubleshooting, GPU setup, and OS-specific details.
* Update README.md
Enhanced installation section with troubleshooting, GPU setup, and OS-specific details.
* Update installation.md
Updated installation.md to include virtual environment and GPU setup instructions.
* Update installation.md
Updated installation.md to include virtual environment and GPU setup instructions.
* Update installation.md
Updated installation.md to include virtual environment, troubleshooting and GPU setup instructions.
* Update installation.md
* Update installation.md
* Update installation.md
* Update installation.md
Updated installation.md to include virtual environment, troubleshooting functions and GPU setup instructions.
* Update installation.md
Updated installation.md to include virtual environment, troubleshooting functions and GPU setup instructions.
* Update installation.md
Updated installation.md to include virtual environment, troubleshooting functions and GPU setup instructions.
* Update README.md
Removed numbering from README.md.
* Update README.md
Removed unnecessary "a)" formatting as per maintainer feedback.
* Update README.md
Added blank lines around code snippets for better readability.
* Update README.md
Removed the line "b) Install a backend framework:" from README.md as per feedback.
* Update README.md
Simplified "For Windows:" to "Windows" in README.md as per feedback as well as "For macOS/Linux:" to "macOS/Linux"
* Update README.md
Removed unnecessary heading and retained valid code snippet.
* Update README.md
Removed unnecessary heading "d) Optional: Install from source for the latest updates" as per feedback.
* Update README.md
Removed "GPU Setup (Optional)" section to align with minimal design feedback.
* Update installation.md
Removed "Create and Activate a Virtual Environment" section from installation.md as per feedback.
* Update installation.md
Adjusted "Troubleshooting" to a second-level heading and added an introductory line as per feedback.
* Update installation.md
Updated troubleshooting section with simplified headings and formatted code blocks as per feedback.
* Update installation.md
Integrated GPU setup instructions into the "Install with pip" section for better content flow.
* Update README.md
Removed Troubleshooting section from README.md for minimalism as per maintainer feedback.
* Update torchao.md: use auto-compilation
* Update torchao.md: indicate updating transformers to the latest
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Add the helium model.
* Add a missing helium.
* And add another missing helium.
* Use float for the rmsnorm mul.
* Add the Helium tokenizer converter.
* Add the pad token as suggested by Arthur.
* Update the RMSNorm + some other tweaks.
* Fix more rebase issues.
* fix copies and style
* fixes and add helium.md
* add missing tests
* udpate the backlink
* oups
* style
* update init, and expected results
* small fixes
* match test outputs
* style fixup, fix doc builder
* add dummies and we should be good to go!z
* update sdpa and fa2 documentation
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
* Create token_classification.md
* Update token_classification.md
* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update docs/source/ar/tasks/token_classification.md
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* Update _toctree.yml
---------
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* model can convert to HF and be loaded back
* nit
* works in single batch generation but hallucinates
* use the image tokens
* add image generation
* now it works
* add tests
* update
* add modulare but it doesn't work for porting docstring :(
* skip some tests
* add slow tests
* modular removed the import?
* guess this works
* update
* update
* fix copies
* fix test
* fix copies
* update
* docs
* fix tests
* last fix tests?
* pls
* repo consistency
* more style
* style
* remove file
* address comments
* tiny bits
* update after the new modular
* fix tests
* add one more cond in check attributes
* decompose down/up/mid blocks
* allow static cache generation in VLMs
* nit
* fix copies
* Update docs/source/en/model_doc/emu3.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/emu3.md
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* Update docs/source/en/model_doc/emu3.md
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* Update docs/source/en/model_doc/emu3.md
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* Update docs/source/en/model_doc/emu3.md
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* Update docs/source/en/model_doc/emu3.md
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* Update docs/source/en/model_doc/emu3.md
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* Update docs/source/en/model_doc/emu3.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix VAE upsampling
* Update src/transformers/models/emu3/modular_emu3.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* address comments
* state overwritten stuff explicitly
* fix copies
* add the flag for flex attn
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* bug fixes
* organize imports
* wrap cpu warning in reference_compile
* Avoid needing repad_logits_with_grad, always repad with grads when training
I'm not 100% that the conditional with "or labels is None" makes sense though - not sure what the intention is there. Perhaps we can remove that?
* Revert "Avoid needing repad_logits_with_grad, always repad with grads when training"
This reverts commit cedcb4e89b.
* Fix grammar: keep -> keeps
* Propagate grammar fix with modular_model_converter
---------
Co-authored-by: Tom Aarsen <Cubiegamedev@gmail.com>
Co-authored-by: Tom Aarsen <37621491+tomaarsen@users.noreply.github.com>
* universal checkpoint
* Update docs/source/en/deepspeed.md
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* Update docs/source/en/deepspeed.md
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* Update docs/source/en/deepspeed.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* إضافة الترجمة العربية: multiple_choice.md
* Update multiple_choice.md
* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update docs/source/ar/tasks/multiple_choice.md
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* Update _toctree.yml
* Add files via upload
* Update _toctree.yml
---------
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* add audio_token attribute to proc
* expand input_ids
* and legacy and expanded input_ids
* test update
* split lines
* add possibility not to provide eos and bos audio tokens
* raise errors
* test incorrect number of audio tokens
* add example
* fmt
* typo
* first adding diffllama
* add Diff Attention and other but still with errors
* complate make attention Diff-Attention
* fix some bugs which may be caused by transformer-cli while adding model
* fix a bug caused by forgetting KV cache...
* Update src/transformers/models/diffllama/modeling_diffllama.py
You don't need to divide by 2 if we use same number of attention heads as llama. instead you can just split in forward.
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
fit to changeing "num_heads // 2" place
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
new codes are more meaningful than before
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
new codes are more meaningful than before
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
fit to changeing "num_heads // 2" place
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
fix 2times divide by sqrt(self.head_dim)
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
fix 2times divide by sqrt(self.head_dim)
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* Update src/transformers/models/diffllama/modeling_diffllama.py
fit to changeing "num_heads // 2" place.
and more visible
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* I found Attention missed implemented from paper still on e072544a3b.
* re-implemented
* adding groupnorm
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* align with transformers code style
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* fix typo
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* adding groupnorm
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* change SdpaAttention to DiffSdpaAttention
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* fix bug
* Update src/transformers/models/diffllama/modeling_diffllama.py
resolve "not same outputs" problem
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* fix bugs of places of "GroupNorm with scale" and etc
* Revert "fix bugs of places of "GroupNorm with scale" and etc"
This reverts commit 26307d92f6.
* simplify multiple of attention (matmul) operations into one by repeating value_states
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* simplify multiple of attention (matmul) operations into one by repeating value_states
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* simplify multiple of attention (matmul) operations into one by repeating value_states
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
* remove missed type
* add diffllama model_doc
* apply make style/quality
* apply review comment about model
* apply review comment about test
* place diffllama alphabetically on the src/transformers/__init__.py
* fix forgot code
* Supports parameters that are not initialized with standard deviation 0 in the conventional method
* add DiffLlamaConfig to CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK on utils/check_config_docstrings.py
* remove unused property of config
* add to supported model list
* add to spda supported model list
* fix copyright, remove pretraining_tensor_parallel, and modify for initialization test
* remove unused import and etc.
* empty commit
* empty commit
* empty commit
* apply modular transformers but with bugs
* revert prev commit
* create src/transformers/model/diffllama/modular_diffllama.py
* run utils/modular_model_converter.py
* empty commit
* leaner modular diffllama
* remove more and more in modular_diffllama.pt
* remove more and more in modular_diffllama.pt
* resolve missing docstring entries
* force reset
* convert modular
---------
Co-authored-by: Minho Ryu <ryumin93@gmail.com>
