* dump
* push other models
* fix simple greedy generation
* xmod
* add fmst and clean up some mentions of old cache format
* gpt-bigcode now follows standards
* delete tuple cache reference in generation
* fix some models
* fix some models
* fix mambas and support cache in tapas
* fix some more tests
* fix copies
* delete `_reorder_cache`
* another fix copies
* fix typos and delete unnecessary test
* fix rag generate, needs special cache reordering
* fix tapas and superglue
* reformer create special cache
* recurrent gemma `reorder_cache` was a no-op, delete
* fix-copies
* fix blio and musicgen pipeline tests
* fix reformer
* fix reformer, again...
* delete `_supports_cache_class`
* delete `supports_quantized_cache`
* fix failing tests
* fix copies
* some minor clean up
* style
* style
* fix copies
* fix tests
* fix copies
* create causal mask now needs positions?
* fixc copies
* style
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* clean-up of non-generative model after merging main
* check `is_decoder` for cache
* delete transpose for scores
* remove tuple cache from docs everywhere
* fix tests
* fix copies
* fix copies once more
* properly deprecate `encoder_attention_mask` in Bert-like models
* import `deprecate_kwarg` where needed
* fix copies again
* fix copies
* delete `nex_decoder_cache`
* fix copies asks to update for PLM
* fix copies
* rebasing had a few new models, fix them and merge asap!
* fix copies once more
* fix slow tests
* fix tests and updare PLM checkpoint
* add read token and revert accidentally removed line
* oh com -on, style
* just skip it, read token has no access to PLM yet
---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* fix vlm with retrieval
* we can't use AutoModel because new ColQwen was released after refactor
* no need for colqwen
* tied weight keys are necessary, if using IMageTextToText
* need to apply renaming in tied weights, only for ColPali
* overwrite tied keys in ColPali
* fix copies, modular can't handle if-statements
* working locally; need to style and test
* added docs and initial tests; need to debug and flesh out
* fixed tests
* working long context; batches
* working fa2 and eager
* update tests
* add missing confnigs
* remove default autoset
* fix spacing
* fix most tests
* fixed tests
* fix to init
* refactor to match new transformers updates
* remove static cache option
* fa2 fix
* fix docs
* in progress
* working on tests
* fixed issue with attn outputs
* remove debug
* fix local config attr
* update doc string
* fix docstring
* add docs to toc
* correct typo in toc
* add new updates from main w.r.t. ModernBERT RoPE
* fix local param
---------
Co-authored-by: oweller2 <oweller2@dsailogin.mgmt.ai.cluster>
Co-authored-by: oweller2 <oweller2@l07.mgmt.ai.cluster>
Co-authored-by: oweller2 <oweller2@n02.mgmt.ai.cluster>
Co-authored-by: oweller2 <oweller2@l08.mgmt.ai.cluster>
Co-authored-by: oweller2 <oweller2@l01.mgmt.ai.cluster>
Co-authored-by: oweller2 <oweller2@l02.mgmt.ai.cluster>
* plm template
* A working plm with fixed image features
* hacked processor
* First version that reproduced PLM output using PE from timm.
* Simplify and fix tie_word_embeddings
* Use PIL resize. Simplify converstion.
* First version that works with video input.
* simplifed image preprocessing (not batched)
* Minor fixes after rebasing on main.
* Video processor based on new API.
* Revert to use _preprocess for image processor.
* refactor with modular
* fix tie_word_embedding
* Testing with timm PE
* check in missed converstion from modular to model.py
* First working version of PLM with Eva PE. PLM-1B and 3B outputs are exactly the same as before. PLM-8B output has some differences.
* address review comments
* Fixed batching if video and image examples mixed.
* Simplify PE configuration.
* Enable AutoModel for PerceptionEncoder.
* Update PE config style.
* update all headers
* Minor fixes.
* Move lm_head to PerceptionLMForConditionalGeneration.
Fix vit_G model specification.
* Fix for testing_modeling_perception_lm.py
* Image processing refactoring to use more common parts.
* Fix processor test.
* update tests to use model from hub
* More test fixes.
* integration test GT update after rebasing; probably due to video preprocessing
* update test media path to hub
* Stop tracking local scripts
* address some review comments
* refactor image processing.
* small fixes
* update documentation and minor fixes
* remove scripts
* Minor fix for CI
* Fix image processing
* CI and doc fix
* CI formatting fix
* ruff fix
* ruff formatting
* ran utils/sort_auto_mappings.py
* update docstring
* more docstring udpates
* add vision_input_type default fallback for image processing
* more verbose variable naming
* test update
* Remove PE and PEConfig use AutoModel(TimmWrapper) instead
* Minor cleanup.
* Minor Fix: remove any ref to PE. Ruff format and check.
* fix docstring
* Fix modular/model consistency.Improvex docstringfor .
* Fix PerceptionLMForConditionalGenerationModelTest
* ruff fix
* fix for check_repo
* minor formatting
* dummy size arg to fix for processor test.
* Update docstring for PerceptionLMConfig
* Minor fixes from review feedback.
* Revert some minor changes per reviewer feedback.
* update base_model_prefix
* address reviewer feedback
* fix comment in modeling file
* address reviewer feedback
* ruff format
* Pre-merge test update.
* reapply modular and fix checkpoint name
* processor test path
* use modular a bit more
* remove dead code
* add token decorator
---------
Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
* changes for video
* update modular
* change get_video_features
* update video token replacement
* update modular
* add test and fix typo
* lint
* fix order
* lint
* fix
* remove dependency
* lint
* lint
* remove todo
* resize video for test
* lint..
* fix test
* new a processor for video_test
* fix test
* add initial structure
* doc fixes, add model base logic
* update init files
* some fixes to config and modular
* some improvements for attention
* format
* remove unused attn
* some fixes for moe layer and for decoder
* adapt _compute_yarn_parameters for deepseek
* format
* small fix
* fix for decoder forward
* add tests, small refactoring
* fix dummies
* fix init
* fix doc
* fix config docs
* add sequce doc, fix init for gate
* fix issues in tests
* fix config doc
* remove unused args
* some fixes and refactoring after review
* fix doc for config
* small fixes for config args
* revert config refactoring
* small refactoring
* minor fixes after rebase
* small fix after merge
* fix modular
* remove rotaryembd from public init
* small test fix
* some rotary pos calculation improvement
* fix format
* some improvements and fixes
* fix config
* some refactoring
* adjust some unit tests
* skip test
* small fixes and tests adjustment
* reapply modular
* fix all tests except Integration
* fix integration testzs
* cleanup BC stuff
* rope
* fix integrations tests based on a10
* style
---------
Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
* Add Doge Model
* Fix code quality
* Rollback an error commit
* Fix config for open-source weights
* Revert "Fix config for open-source weights"
This reverts commit 229cdcac10a6a4274d1dd13b729bc14c98eb0c76.
* Add modular_doge
* Update Doge inherits from Llama
* Fix import bug
* [docs] Add usage of doge model
* Fix Doge import pretrainedconfig from modeling_utils to configuration_utils
* [docs] remove trust remote code from doge
* Fix dynamo bug in doge model
* Update docstrings
* Import apply_rotary_pos_emb and repeat_kv from Llama
* Fix all nits
* Fix code quality
* Fix some bugs
* Fix code quality
* Remove inherited `_update_causal_mask` from Llama
This leads to incorrect weight initialization.
* Fix the wrong tensor orderings in DogeCDMoE
* Fix attention mask bug
We have to provide attention_mask for dynamic mask computation
* Modify most implementations to inherit from Llama
But there are two problems:
1. `flex_attention_forward` is not updated properly
2. `Example` error in the forward method of DogeForCausalLM
* Modify CDMoE for batch efficient implementation
* Uniform MoE configuration names, just like QwenMoE
* Fix code quality
* Fix code quality
* Fix code quality
* Add tp plan of CDMoE Module
* Hybird DMA with sliding window
* Update valid tokens greater than window size
* Fix code quality
* Add `convert_doge_weights_to_hf`
* Fix STATE_DICT_MAPPING in convert_doge_weights_to_hf.py
* Fix nits in modular_doge
* Fix code quality
* Fix all nits
* Fix all nits
* Make sure the attention function is updated inside the class
* Fix code quality issues in the Doge model and add a test for it
* Fix `test_generate`
* Fix code quality
* Fix nits fllowing suggestions
* Fix code quality
* Fix code quality issues
* Fix nits
* Fix code quality nits
* Fix the missing parameters in the configuration.
* Fix the missing parameters in the configuration.
* Fix nits
* Add initialization of attention
* Fix last nits
* Simplify dynamic mask generation logic
* Rename router_logits to gate_logits for matching latest changes of MixtralModel
* Rename typings for matching latest changes of MixtralModel
* Fixes typo in comment
* Update src/transformers/models/doge/modular_doge.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Fix code quality issues to match other modular
* Fix code quality issues to match other modular
* Fix the static compilation errors
* Update model weights link
* Fix code quality issues to match other modular
* reapply modular and support for new outputs
* style
* simplify a lot
* fix import location
* reapply modular
* fix
* fix integration test
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
* chameleon xpu bnb groundtruth update on bnb triton backend since we are
deprecating ipex backend
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* enable hqq uts on XPU, all passed
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix comment
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* update the glm4 model readme
* update test
* update GLM-4.1V model
* update as format
* update
* fix some tests
* fix the rest
* fix on a10, not t4
* nit: dummy import
---------
Co-authored-by: raushan <raushan@huggingface.co>
* just update 2 files
* update other models as well just making fix-copies
* also add the changes needed to modeling utils
* put this on the pretrained model instead
* nits and fixes
* update generic, fix to use config value
* update other modelings
* use transformers kwargs instead
* update
* update
* update other models
* update
* updates
* update
* update
* update
* fix
* finally
* very small nits
* this fixes more tests
* fix other models as well!
* update modularqwen2
* update models based on qwen2
* update
* update
* remove the **flash stuff in favor of noraml kwargs
* update
* propagate gemma?
* remove output attentions
* propagate
* support cross attention edge case
* same
* test this
* fixes
* more fix
* update
* update
* fix conflicts
* update
* fix emu3
* fix emu3
* move the fix a bit
* quel enfer
* some fixes, loss_kwargs should never had been
* finish fixing gemma3n
* fix small lm3
* fix another one
* fix csm now
* fux csm and mistral
* fix mistral now
* small fixes
* fix janusss
* only for some models
* fixup
* phix phi3
* more fixes?
* dose this fix it?
* update
* holy shit it was just graph breaks
* protect torch
* updates
* fix samhq?
* fix moonshine
* more moonshine fixes, 3 failures left!
* nits
* generic needs to support more
* more fixes to moonshine!
* fix cross attention outputs!
* fix csm!
* nits
* fix stupid kosmos2
* current updates
* fixes
* use output recorder?
* nicer!
* a little bit of magic
* update
* fix protect
* fix
* small fixes
* protect import
* fix a bunch of more models
* fix fixups
* fix some of the last ones
* nit
* partly fix phi
* update
* fix import path
* make something that is fullgraph compatible just to be sure
* typing was wrong on llama so the rest was wrong as well
* fucking ugly but at least it is still exportable
* syle
* supposed to fix moonshine, it still breaks
* fix some default
* fix the last bits of sam
* update samhq
* more fixes to am hq
* nit
* fix all output+hidden states and output_attentions!
* fix?
* fix diffllama
* updates to fix initialization on the sam pips
* ups there was a bug
* fix the last sam hq test
* fix gotocr
* fix gotocr2!
* fixes
* skip stupid tests
* there was one left :)
* fixup
* fix fix copies issues with this test file
* fix copies for sam_hq
* rm some comments
* skip 2 more failing tests
* fix
* fix everything
* Apply suggestions from code review
Co-authored-by: Anton Vlasjuk <73884904+vasqu@users.noreply.github.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
* add more doc!
* fix public init
* fix modular qwen3
---------
Co-authored-by: Anton Vlasjuk <73884904+vasqu@users.noreply.github.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
* Expectations for llava_next_video
* Updated image src in aria
* Fix test_small_model_integration_test
* Fix small model integration llama
* Fix a bunch of tests
* Style
* Shortened generation in test from 900 to 90
* Fixed some devices errors
* Fixed other device issues and more expectations
* Reverted support flags
* style
* More granular support
* Fixed some rebase stuff
* add a not None check before .to
* fix FA2
* update is causal flag and remove mask for FA2
* update for FA2 with varlen path
* how the tests were passing with different devices?
* add comment and ref to the PR
* move mask preparation to base pretrained model
* seq len is the first dim, not second
* fix copies to fix GLM4V
* deprecate for 1 version
* style
* fix some tests
* fix esm
* skip for now, GC requires positional args but we have keyword args
* remove transpose for scores in modified models only
* skip fx trace tests
* remove the skips
* fix the epsilon to a small value (does not make sense otherwise)
* safeguard
* overload test_eager_matches_sdpa
* Update test_modeling_common.py
* skip appropriate tests
* correct no_split_layer
* fix all devices issue
* fix backward
* fix
* Add Fast Image Processor for Chameleon
* add warning to resize and move blend_rgba to convert_to_rgb
* Remove unrelated files
* Update image_processing_chameleon_fast to use auto_docstring
* fix equivalence test
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
