* initial design
* update all video processors
* add tests
* need to add qwen2-vl (not tested yet)
* add qwen2-vl in auto map
* fix copies
* isort
* resolve confilicts kinda
* nit:
* qwen2-vl is happy now
* qwen2-5 happy
* other models are happy
* fix copies
* fix tests
* add docs
* CI green now?
* add more tests
* even more changes + tests
* doc builder fail
* nit
* Update src/transformers/models/auto/processing_auto.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* small update
* imports correctly
* dump, otherwise this is getting unmanagebale T-T
* dump
* update
* another update
* update
* tests
* move
* modular
* docs
* test
* another update
* init
* remove flakiness in tests
* fixup
* clean up and remove commented lines
* docs
* skip this one!
* last fix after rebasing
* run fixup
* delete slow files
* remove unnecessary tests + clean up a bit
* small fixes
* fix tests
* more updates
* docs
* fix tests
* update
* style
* fix qwen2-5-vl
* fixup
* fixup
* unflatten batch when preparing
* dump, come back soon
* add docs and fix some tests
* how to guard this with new dummies?
* chat templates in qwen
* address some comments
* remove `Fast` suffix
* fixup
* oops should be imported from transforms
* typo in requires dummies
* new model added with video support
* fixup once more
* last fixup I hope
* revert image processor name + comments
* oh, this is why fetch test is failing
* fix tests
* fix more tests
* fixup
* add new models: internvl, smolvlm
* update docs
* imprt once
* fix failing tests
* do we need to guard it here again, why?
* new model was added, update it
* remove testcase from tester
* fix tests
* make style
* not related CI fail, lets' just fix here
* mark flaky for now, filas 15 out of 100
* style
* maybe we can do this way?
* don't download images in setup class
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Add fast image processor support for Swin2SR
* Add Swin2SR tests of fast image processing
* Update docs and remove unnecessary test func
* Fix docstring formatting
* Skip fast vs slow processing test
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* i guessreverted all CdGen classes
* style
* llava onevision
* fix copies
* fix some tests
* some more tests
* dump
* skip these
* nevermind, i am dumb
* revert fix not needed
* fixup
* fixup
* another fixup
* more fixup to make ci finally happy
* fixup after rebasing
* fix qwen tests
* add internVL + typos here and there
* image token index -> id
* style
* fix init weights
* revert blip-2 not supported
* address comments
* fix copies
* revert blip2 test file as well
* as discussed internally, revert back CdGen models
* fix some tests
* fix more tests for compile
* CI red
* fix copies
* enumerate explicitly allowed models
* address comments
* fix tests
* fixup
* style again
* add tests for new model class
* another fixup ( x _ x )
* [fixup] unused attributes can be removed post-deprecation
* aligning for vllm
* using input shape rather than attn outputs
* remove demo
* revert Conv1D
* style
* style
* Update src/transformers/models/gpt2/modeling_gpt2.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix copies
* Apply suggestions from code review
Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
* adding docs about vllm
* chore: style
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
* copy the last changes from broken PR
* small format
* some fixes and refactoring after review
* format
* add config attr for loss
* some fixes and refactoring
* fix copies
* fix style
* add test for d-fine resnet
* fix decoder layer prop
* fix dummies
* format init
* remove extra print
* refactor modeling, move resnet into separate folder
* fix resnet config
* change resnet on hgnet_v2, add clamp into decoder
* fix init
* fix config doc
* fix init
* fix dummies
* fix config docs
* fix hgnet_v2 config typo
* format modular
* add image classification for hgnet, some refactoring
* format tests
* fix dummies
* fix init
* fix style
* fix init for hgnet v2
* fix index.md, add init rnage for hgnet
* fix conversion
* add missing attr to encoder
* add loss for d-fine, add additional output for rt-detr decoder
* tests and docs fixes
* fix rt_detr v2 conversion
* some fixes for loos and decoder output
* some fixes for loss
* small fix for converted modeling
* add n model config, some todo comments for modular
* convert script adjustments and fixes, small refact
* remove extra output for rt_detr
* make some outputs optionsl, fix conversion
* some posr merge fixes
* small fix
* last field fix
* fix not split for hgnet_v2
* disable parallelism test for hgnet_v2 image classification
* skip multi gpu for d-fine
* adjust after merge init
* remove extra comment
* fix repo name references
* small fixes for tests
* Fix checkpoint path
* Fix consistency
* Fixing docs
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* added fast image processor for VitMatte including updated and new tests, fixed a bug in the slow image processor that processed images incorrectly for input format ChannelDimension.FIRST in which case the trimaps were not added in the correct dimension, this bug was also reflected in the tests through incorretly shaped trimaps being passed
* final edits for fast vitmatte image processor and tests
* final edits for fast vitmatte image processor and tests
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* added the configuartion for sam_hq
* added the modeelling for sam_hq
* added the sam hq mask decoder with hq features
* added the code for the samhq
* added the code for the samhq
* added the code for the samhq
* Delete src/transformers/models/sam_hq/modelling_sam_hq.py
* added the code for the samhq
* added the code for the samhq
* added the chnages for the modeelling
* added the code for sam hq for image processing
* added code for the sam hq model
* added the required changes
* added the changes
* added the key mappings for the sam hq
* adding the working code of samhq
* added the required files
* adding the pt object
* added the push to hub account
* added the args for the sam maks decoder
* added the args for the sam hq vision config
* aded the some more documentation
* removed the unecessary spaces
* all required chnages
* removed the image processor
* added the required file
* added the changes for the checkcopies
* added the code for modular file
* added the changes for the __init file
* added the code for the interm embeds
* added the code for sam hq
* added the changes for modular file
* added the test file
* added the changes required
* added the changes required
* added the code for the
* added the cl errors
* added the changes
* added the required changes
* added the some code
* added the code for the removing image processor
* added the test dimensins
* added the code for the removing extra used variables
* added the code for modeluar file hf_mlp for a better name
* removed abbrevaation in core functionality
* removed abbrevaation in core functionality
* .contiguous() method is often used to ensure that the tensor is stored in a contiguous block of memory
* added the code which is after make fixup
* added some test for the intermediate embeddings test
* added the code for the torch support in sam hq
* added the code for the updated modular file
* added the changes for documentations as mentioned
* removed the heading
* add the changes for the code
* first mentioned issue resolved
* added the changes code to processor
* added the easy loading to init file
* added the changes to code
* added the code to changes
* added the code to work
* added the code for sam hq
* added the code for sam hq
* added the code for the point pad value
* added the small test for the image embeddings and intermediate embedding
* added the code
* added the code
* added the code for the tests
* added the code
* added ythe code for the processor file
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code for tests and some checks
* added some code
* added the code
* added the code
* added some code
* added some code
* added the changes for required
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added some changes
* added some changes
* removed spaces and quality checks
* added some code
* added some code
* added some code
* added code quality checks
* added the checks for quality checks
* addded some code which fixes test_inference_mask_generation_no_point
* added code for the test_inference_mask_generation_one_point_one_bb
* added code for the test_inference_mask_generation_one_point_one_bb_zero
* added code for the test_inference_mask_generation_one_box
* added some code in modelling for testing
* added some code which sort maks with high score
* added some code
* added some code
* added some code for the move KEYS_TO_MODIFY_MAPPING
* added some code for the unsqueeze removal
* added some code for the unsqueeze removal
* added some code
* added some code
* add some code
* added some code
* added some code
* added some testign values changed
* added changes to code in sam hq for readbility purpose
* added pre commit checks
* added the fix samvisionmodel for compatibilty
* added the changes made on sam by cyyever
* fixed the tests for samhq
* added some the code
* added some code related to init file issue during merge conflicts
* remobved the merge conflicts
* added changes mentioned by aruther and mobap
* added changes mentioned by aruther and mobap
* solving quality checks
* added the changes for input clearly
* added the changes
* added changes in mask generation file rgearding model inputs and sam hq quargs in processor file
* added changes in processor file
* added the Setup -> setupclass conversion
* added the code mentioned for processor
* added changes for the code
* added some code
* added some code
* added some code
---------
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
* update siglip2 model card
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* address comments
* separate naflex and fixres variant
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip2.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fast image processor template for MobileNetV1 via transformers-cli
* Add fast image processors and unify tests for slow/fast image processor classes
* added loop over image_processor_list for all tests and removed boilerplate comments.
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* support poolformer fast image processor
* support test for crop_pct=None
* run make style
* Apply suggestions from code review
* rename test
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* new card for mbart and mbart50
* removed comment BADGES
* Update mBart overview
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix typo (MBart to mBart)
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* maybe fix typo
* update typo and combine notes
* changed notes
* changed the example sentence
* fixed grammatical error and removed some lines from notes example
* missed one word
* removed documentation resources and added some lines of example code back in notes.
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Added documentation for phi model
* Update phi.md
* Update phi.md
* Update phi.md
* Update docs/source/en/model_doc/phi.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/phi.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/phi.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/phi.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Updated model card
* Update phi.md
* Update phi.md
* Update phi.md
* Update docs/source/en/model_doc/phi.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Jihad <jihadhammoud_@hotmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update longformer.md
* Update longformer.md
* Update docs/source/en/model_doc/longformer.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/longformer.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update longformer.md
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* edit siglip model card
* fix syntax
* Update docs/source/en/model_doc/siglip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/siglip.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* address comments
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 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 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
---------
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* 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
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* Update docs/source/en/model_doc/vits.md
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* Update docs/source/en/model_doc/vits.md
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* Update vits.md
---------
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* 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
---------
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* 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
---------
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* support flava fast image processor
* run style and quality
* update test
* update according to reviews
* make style
* update comment on BICUBIC
* make style
---------
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* 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
---------
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* 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
* add changed
* Revert "add changed"
This reverts commit 0a0166a1fe.
* update with NEW MODEL class called GLM4
* update
* Update glm4.md
* Name
* style
* fix copies
* fixup test
---------
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* Updated documentation for Donut model
* Update docs/source/en/model_doc/donut.md
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* Update docs/source/en/model_doc/donut.md
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* Update docs/source/en/model_doc/donut.md
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* Update docs/source/en/model_doc/donut.md
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* Updated code suggestions
* Update docs/source/en/model_doc/donut.md
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* Updated code suggestion to Align with the AutoModel example
* Update docs/source/en/model_doc/donut.md
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* Updated notes section included code examples
* close hfoption block and indent
---------
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* Update model card for jamba
* Apply the suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Apply suggestions from code review-2
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* update model page.
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update as per code review.
* Update docs/source/en/model_doc/jamba.md as per code review
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* Update docs/source/en/model_doc/jamba.md as per code review
`
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* update as per code review.
* fixes
---------
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* 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
* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Update OpenAI GPT model card: add usage examples and notes section
* Add API autodoc tags after Notes section for OpenAI GPT model
* Update docs/source/en/model_doc/openai-gpt.md
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* Update docs/source/en/model_doc/openai-gpt.md
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* Added missing badges
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* Updated T5 model card with standardized format
* Updated T5 model card with standardized format, fixed typo
* Update docs/source/en/model_doc/t5.md
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* 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
* Update docs/source/en/model_doc/code_llama.md
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* Update docs/source/en/model_doc/code_llama.md
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* make changes as per code review
* chore: make the function smaller for attention mask visualizer
* chore[docs]: update code_llama.md with some more suggested changes
* Update docs/source/en/model_doc/code_llama.md
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* chore[docs] : Update code_llama.md with indentation changes
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* Update Cohere model card to follow standard template
* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update docs/source/en/model_doc/cohere.md
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* Update cohere.md
Update code snippet for AutoModel, quantization, and transformers-cli
* Update cohere.md
* Update docs/source/en/model_doc/cohere.md
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---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* feat: updated model card for qwen_2.5_vl
* applied suggested change 1
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* applied suggested change 2
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* applied suggested change 3
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix: made requested changes for quantization and notes
* suggeested model card change 4
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* updated model card wiht suggested change 5
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* updated model card wiht suggested change 6
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* updated model card wiht suggested change 7
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* feat: applied requested changes
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update qwen2.md
* Update qwen2.md
* Update qwen2.md
* Update qwen2.md
* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update qwen2.md
* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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* Update docs/source/en/model_doc/qwen2.md
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---------
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
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* Update docs/source/en/model_doc/falcon.md
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* fix: Add suggested changes
* fix: typo in link for quantization
* Update docs/source/en/model_doc/falcon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/model_doc/falcon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix: fix indent and close ticks
* fix: add indent
---------
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* Update clip.md
* Update docs/source/en/model_doc/clip.md
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* Update docs/source/en/model_doc/clip.md
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* Update docs/source/en/model_doc/clip.md
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* Incorporated suggested changes
* Update docs/source/en/model_doc/clip.md
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* Update docs/source/en/model_doc/clip.md
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* Update docs/source/en/model_doc/clip.md
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---------
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>
* 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>
* 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>
* 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>
