Update generation_strategies.md
The prompt text shown in the example does not match what is inside the generated output. As the generated output always include the prompt, the correct prompt should be "Hugging Face is an open-source company".
* initial commit
* add convert internvl
* add first end-to-end working internvl
* nit prompt and image proc
* add working chat template
* add conversion llama-based models
* add tests
* pass all tests
* fix isort
* fix modular after main merge
* add video processing for internvl
* add support for interlaced images and videos
* Remove processing and config from modular, add more tests
* add llama model tests
* Modify processor for compatibility with refactored got ocr image processor
* add comments in processor
* Add docs and nits
* change video processing to use custom sample_indices_fn
* rebase and fix tests
* add processor tests
* Add changes Raushan review
* Use the new attention interface for the vision model
* nits
* add support for custom video_load_backend
* remove mention to InternVLTokenizer
* refactor vision model to simplify logic
* refactor processor for better readibility
* fix copies
* fix require av processor test
* refactor internVL vision
* Update processor and fix processing tests
* fix docstring
* update convert_weights for internvl3
* change image processor to fast by default
* remove do_center_crop=True in convert_weights
* force use_cache to True
* push_to_hub before reloading
* fix internVLVision for larger models
* update convert weight for qk norm
* fix convert_weights
* fix eos_token_id in convert
* update docs and integration tests
* make modifs after review
* fix wrong k_norm and reduce modular
* change image_token_index to image_token_id
* change checkpoint to OpenGVLab org
* last nits
* explicitely del self.num_key_value_groups
* add extra special tokens
* 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
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* add links to each quant method page
* separate calibration vs no calibration methods
* add calibration time estimates
---------
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* 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
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* Updated code suggestion to Align with the AutoModel example
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* Updated notes section included code examples
* close hfoption block and indent
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* Update model card for jamba
* Apply the suggestions from code review
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* Apply suggestions from code review-2
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* update model page.
* Apply suggestions from code review
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* Update as per code review.
* Update docs/source/en/model_doc/jamba.md as per code review
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* Update docs/source/en/model_doc/jamba.md as per code review
`
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* update as per code review.
* fixes
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* Improved Model card for Gemma2
* Made changes in gemma2 as suggested
* Made more changes in the doc (adding image, notes, closing hfoptions)
* minor fixes
---------
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* 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
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* 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
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* 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
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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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* Added missing badges
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* Updated T5 model card with standardized format
* Updated T5 model card with standardized format, fixed typo
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* Update docs/source/en/model_doc/t5.md
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* Apply reviewer suggestions
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* 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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* Update ELECTRA model card with new format
* Update ELECTRA model card with new format
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* Update docs/source/en/model_doc/electra.md
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* close hfoption block
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* Modify Model Card for ModernBERT.
* Update as per code review.
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* Update model card.
* Update model card.
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* 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
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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
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* Update docs/source/en/model_doc/cohere.md
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* Update cohere.md
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* feat: updated model card for qwen_2.5_vl
* applied suggested change 1
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* applied suggested change 2
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* applied suggested change 3
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* fix: made requested changes for quantization and notes
* suggeested model card change 4
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* updated model card wiht suggested change 5
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* updated model card wiht suggested change 6
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* updated model card wiht suggested change 7
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* feat: applied requested changes
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* Update qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* feat: updated model card for falcon
* fix:rewrite model description
* fix: add link to conversion script
* 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>
* 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>
* 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>
* 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: 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
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 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
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 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
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 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
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
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 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>
