* HQQ model serialization attempt
* fix hqq dispatch and unexpected keys
* style
* remove check_old_param
* revert to check HQQLinear in quantizer_hqq.py
* revert to check HQQLinear in quantizer_hqq.py
* update HqqConfig default params
* make ci happy
* make ci happy
* revert to HQQLinear check in quantizer_hqq.py
* check hqq_min version 0.2.0
* set axis=1 as default in quantization_config.py
* validate_env with hqq>=0.2.0 version message
* deprecated hqq kwargs message
* make ci happy
* remove run_expected_keys_check hack + bump to 0.2.1 min hqq version
* fix unexpected_keys hqq update
* add pre_quantized check
* add update_expected_keys to base quantizerr
* ci base.py fix?
* ci base.py fix?
* fix "quantization typo" src/transformers/utils/quantization_config.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix post merge
---------
Co-authored-by: Marc Sun <marc@huggingface.co>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Enable non-safetensor serialization and deserialization for TorchAoConfig quantized model
Summary:
After https://github.com/huggingface/huggingface_hub/pull/2440 we added non-safetensor serialization and deserialization
in huggingface, with this we can now add the support in transformers
Note that we don't plan to add safetensor serialization due to different goals of wrapper tensor subclass and safetensor
see README for more details
Test Plan:
tested locally
Reviewers:
Subscribers:
Tasks:
Tags:
* formatting
* formatting
* minor fix
* formatting
* address comments
* comments
* minor fix
* update doc
* refactor compressed tensor quantizer
* add bloom arch support for gguf
* apply format
* small refactoring, bug fix in GGUF_TENSOR_MAPPING naming
* optimize bloom GGUF_TENSOR_MAPPING
* implement reverse reshaping for bloom gguf
* add qkv weights test
* add q_8 test for bloom
Update siglip.md
This was already partially fixed relative to the deployed docs. But the partial fix made it inconsistent. Additionally, giving the full text ("This is a photo of...") is likely not the desired output.
* Add Idefics 3!
* fixes to make both pipelines identical
* fix for quantized models
* First pass at the review
* remove vocab size from the main config (it's still in the text_config)
* hot fix for merve
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* re-add model_type for text_config
* remove support for old_cache
* remove hidden_size from main config
* rename idefics3 HF repo
* few changes suggested in the PR
* fix to input_data_format computation
* remove overwrite of _autoset_attn_implementation following @zucchini-nlp suggestion
* improve example
* few improvements from amy's review
* big change to enable processing input images as numpy arrays
* Changes to the code to uniformize processor kwargs
* image processing tests
* image processing tests fixes and some bugs they discovered
* addressed review comments from Yoni
* fix modeling tests
* remove special tokens that are not special
* fixes tests
* skip failing tests - they also fail for idefics2
* added paper and readded the tests with multi gpu, who knows
* Update docs/source/en/model_doc/idefics3.md
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>
* review amy until image_processing_idefics3
* last comments from Amy
* review amy
* Update src/transformers/models/idefics3/image_processing_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/idefics3/modeling_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update docs/source/en/model_doc/idefics3.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* doc improvement - amy review
* fix runtime error during fine-tuning
* amy's review
* Update src/transformers/models/idefics3/image_processing_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/idefics3/image_processing_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/idefics3/modeling_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* ruff
* amy's comment on the order
* ruff ruff
* fix copies
* square images when they are not splitted
* ruff :(
* Update src/transformers/models/idefics3/image_processing_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics3/test_processing_idefics3.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix small bug introduced in refactor
* amy's image processing changes
* fixes peft tests and ruff
* modify to_pil_image from transformers. and review from emanuele.
* add modified to_pil_image
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add compressed-tensors HFQuantizer implementation
* flag serializable as False
* run
* revive lines deleted by ruff
* fixes to load+save from sparseml, edit config to quantization_config, and load back
* address satrat comment
* compressed_tensors to compressed-tensors and revert back is_serializable
* rename quant_method from sparseml to compressed-tensors
* tests
* edit tests
* clean up tests
* make style
* cleanup
* cleanup
* add test skip for when compressed tensors is not installed
* remove pydantic import + style
* delay torch import in test
* initial docs
* update main init for compressed tensors config
* make fix-copies
* docstring
* remove fill_docstring
* Apply suggestions from code review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* review comments
* review comments
* comments - suppress warnings on state dict load, tests, fixes
* bug-fix - remove unnecessary call to apply quant lifecycle
* run_compressed compatability
* revert changes not needed for compression
* no longer need unexpected keys fn
* unexpected keys not needed either
* Apply suggestions from code review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* add to_diff_dict
* update docs and expand testing
* Update _toctree.yml with compressed-tensors
* Update src/transformers/utils/quantization_config.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* update doc
* add note about saving a loaded model
---------
Co-authored-by: George Ohashi <george@neuralmagic.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Sara Adkins <sara@neuralmagic.com>
Co-authored-by: Sara Adkins <sara.adkins65@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Dipika Sikka <ds3822@columbia.edu>
Co-authored-by: Dipika <dipikasikka1@gmail.com>
* update exampel
* update
* push the converted diff files for testing and ci
* correct one example
* fix class attributes and docstring
* nits
* oups
* fixed config!
* update
* nitd
* class attributes are not matched against the other, this is missing
* fixed overwriting self.xxx now onto the attributes I think
* partial fix, now order with docstring
* fix docstring order?
* more fixes
* update
* fix missing docstrings!
* examples don't all work yet
* fixup
* nit
* updated
* hick
* update
* delete
* update
* update
* update
* fix
* all default
* no local import
* fix more diff
* some fix related to "safe imports"
* push fixed
* add helper!
* style
* add a check
* all by default
* add the
* update
* FINALLY!
* nit
* fix config dependencies
* man that is it
* fix fix
* update diffs
* fix the last issue
* re-default to all
* alll the fixes
* nice
* fix properties vs setter
* fixup
* updates
* update dependencies
* make sure to install what needs to be installed
* fixup
* quick fix for now
* fix!
* fixup
* update
* update
* updates
* whitespaces
* nit
* fix
* simplify everything, and make it file agnostic (should work for image processors)
* style
* finish fixing all import issues
* fixup
* empty modeling should not be written!
* Add logic to find who depends on what
* update
* cleanup
* update
* update gemma to support positions
* some small nits
* this is the correct docstring for gemma2
* fix merging of docstrings
* update
* fixup
* update
* take doc into account
* styling
* update
* fix hidden activation
* more fixes
* final fixes!
* fixup
* fixup instruct blip video
* update
* fix bugs
* align gemma2 with the rest as well
* updats
* revert
* update
* more reversiom
* grind
* more
* arf
* update
* order will matter
* finish del stuff
* update
* rename to modular
* fixup
* nits
* update makefile
* fixup
* update order of the checks!
* fix
* fix docstring that has a call inside
* fiix conversion check
* style
* add some initial documentation
* update
* update doc
* some fixup
* updates
* yups
* Mostly todo gimme a minut
* update
* fixup
* revert some stuff
* Review docs for the modular transformers (#33472)
Docs
* good update
* fixup
* mmm current updates lead to this code
* okay, this fixes it
* cool
* fixes
* update
* nit
* updates
* nits
* fix doc
* update
* revert bad changes
* update
* updates
* proper update
* update
* update?
* up
* update
* cool
* nits
* nits
* bon bon
* fix
* ?
* minimise changes
* update
* update
* update
* updates?
* fixed gemma2
* kind of a hack
* nits
* update
* remove `diffs` in favor of `modular`
* fix make fix copies
---------
Co-authored-by: Lysandre Debut <hi@lysand.re>
* enable cpu bnb path
* fix style
* fix code style
* fix 4 bit path
* Update src/transformers/utils/import_utils.py
Co-authored-by: Aarni Koskela <akx@iki.fi>
* add multi backend refactor tests
* fix style
* tweak 4bit quantizer + fix corresponding tests
* tweak 8bit quantizer + *try* fixing corresponding tests
* fix dequant bnb 8bit
* account for Intel CPU in variability of expected outputs
* enable cpu and xpu device map
* further tweaks to account for Intel CPU
* fix autocast to work with both cpu + cuda
* fix comments
* fix comments
* switch to testing_utils.torch_device
* allow for xpu in multi-gpu tests
* fix tests 4bit for CPU NF4
* fix bug with is_torch_xpu_available needing to be called as func
* avoid issue where test reports attr err due to other failure
* fix formatting
* fix typo from resolving of merge conflict
* polish based on last PR review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* fix CI
* Update src/transformers/integrations/integration_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/integrations/integration_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix error log
* fix error msg
* add \n in error log
* make quality
* rm bnb cuda restriction in doc
* cpu model don't need dispatch
* fix doc
* fix style
* check cuda avaliable in testing
* fix tests
* Update docs/source/en/model_doc/chameleon.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update docs/source/en/model_doc/llava_next.md
Co-authored-by: Aarni Koskela <akx@iki.fi>
* Update tests/quantization/bnb/test_4bit.py
Co-authored-by: Aarni Koskela <akx@iki.fi>
* Update tests/quantization/bnb/test_4bit.py
Co-authored-by: Aarni Koskela <akx@iki.fi>
* fix doc
* fix check multibackends
* fix import sort
* remove check torch in bnb
* docs: update bitsandbytes references with multi-backend info
* docs: fix small mistakes in bnb paragraph
* run formatting
* reveret bnb check
* move bnb multi-backend check to import_utils
* Update src/transformers/utils/import_utils.py
Co-authored-by: Aarni Koskela <akx@iki.fi>
* fix bnb check
* minor fix for bnb
* check lib first
* fix code style
* Revert "run formatting"
This reverts commit ac108c6d6b.
* fix format
* give warning when bnb version is low and no cuda found]
* fix device assignment check to be multi-device capable
* address akx feedback on get_avlbl_dev fn
* revert partially, as we don't want the function that public, as docs would be too much (enforced)
---------
Co-authored-by: Aarni Koskela <akx@iki.fi>
Co-authored-by: Titus von Koeller <9048635+Titus-von-Koeller@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add sdpa to dinov2
* fixup
* add dinov2 to sdpa doc
* update doc order
* [run-slow] dinov2
* common to eager
* [run-slow] dinov2
* update attn implementation in common
* update test_modeling_dinov2 to have mask_ration, num_masks and mask_length similar to vit
* [run-slow] dinov2
---------
Co-authored-by: Avishai Elmakies <avishai.elma@cs.huji.ac.il>
* clean mimi commit
* some nits suggestions from Arthur
* make fixup
* rename repo id + change readme
* Update docs/source/en/model_doc/mimi.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add flaky flag to batching equivalence due to audio_codes failing sometimes
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add explicit example for RAG chat templating
* Add Tip box and reformulate
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
---------
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Update ar lang build_documentation.yml
* Update ar lang build_pr_documentation.yml
* Update docs/source/ar/pipeline_tutorial.md
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* Update docs/source/ar/pipeline_tutorial.md
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* Update docs/source/ar/pipeline_tutorial.md
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* Update docs/source/ar/pipeline_tutorial.md
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* Update docs/source/ar/pipeline_tutorial.md
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---------
Co-authored-by: Abdullah Mohammed <554032+abodacs@users.noreply.github.com>
* initial commit
* gloups
* updates
* work
* weights match
* nits
* nits
* updates to support the tokenizer :)
* updates
* Pixtral processor (#33454)
* rough outline
* Add in image break and end tokens
* Fix
* Udo some formatting changes
* Set patch_size default
* Fix
* Fix token expansion
* nit in conversion script
* Fix image token list creation
* done
* add expected results
* Process list of list of images (#33465)
* updates
* working image and processor
* this is the expected format
* some fixes
* push current updated
* working mult images!
* add a small integration test
* Uodate configuration docstring
* Formatting
* Config docstring fix
* simplify model test
* fixup modeling and etests
* Return BatchMixFeature in image processor
* fix some copies
* update
* nits
* Update model docstring
* Apply suggestions from code review
* Fix up
* updates
* revert modeling changes
* update
* update
* fix load safe
* addd liscence
* update
* use pixel_values as required by the model
* skip some tests and refactor
* Add pixtral image processing tests (#33476)
* Image processing tests
* Add processing tests
* woops
* defaults reflect pixtral image processor
* fixup post merge
* images -> pixel values
* oups sorry Mr docbuilder
* isort
* fix
* fix processor tests
* small fixes
* nit
* update
* last nits
* oups this was really breaking!
* nits
* is composition needs to be true
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add xpu note
* add one more case
* add more
* Update docs/source/en/run_scripts.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Make StaticCache configurable at model construct time
* integrations import structure
* add new doc file to toc
---------
Co-authored-by: Guang Yang <guangyang@fb.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
* Update docs for GGUF supported models
* Add tensor mappings and define class GGUFPhi3Converter
* Fix tokenizer
* Working version
* Attempt to fix some CI failures
* Run ruff format
* Add vocab, merges, decoder methods like LlamaConverter
* Resolve conflicts since Qwen2Moe was added to gguf
- I missed one place when resolving conflict
- I also made a mistake with tests_ggml.py and now has been fixed to reflect
its master version.
* Fixed typo: insted to instead
* Fixed typo: relase to release
* Fixed typo: nighlty to nightly
* Fixed typos: versatible, benchamarks, becnhmark to versatile, benchmark, benchmarks
* Fixed typo in comment: quantizd to quantized
* Fixed typo: architecutre to architecture
* Fixed typo: contibution to contribution
* Fixed typo: Presequities to Prerequisites
* Fixed typo: faste to faster
* Fixed typo: extendeding to extending
* Fixed typo: segmetantion_maps to segmentation_maps
* Fixed typo: Alternativelly to Alternatively
* Fixed incorrectly defined variable: output to output_disabled
* Fixed typo in library name: tranformers.onnx to transformers.onnx
* Fixed missing import: import tensorflow as tf
* Fixed incorrectly defined variable: token_tensor to tokens_tensor
* Fixed missing import: import torch
* Fixed incorrectly defined variable and typo: uromaize to uromanize
* Fixed incorrectly defined variable and typo: uromaize to uromanize
* Fixed typo in function args: numpy.ndarry to numpy.ndarray
* Fixed Inconsistent Library Name: Torchscript to TorchScript
* Fixed Inconsistent Class Name: OneformerProcessor to OneFormerProcessor
* Fixed Inconsistent Class Named Typo: TFLNetForMultipleChoice to TFXLNetForMultipleChoice
* Fixed Inconsistent Library Name Typo: Pytorch to PyTorch
* Fixed Inconsistent Function Name Typo: captureWarning to captureWarnings
* Fixed Inconsistent Library Name Typo: Pytorch to PyTorch
* Fixed Inconsistent Class Name Typo: TrainingArgument to TrainingArguments
* Fixed Inconsistent Model Name Typo: Swin2R to Swin2SR
* Fixed Inconsistent Model Name Typo: EART to BERT
* Fixed Inconsistent Library Name Typo: TensorFLow to TensorFlow
* Fixed Broken Link for Speech Emotion Classification with Wav2Vec2
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed minor missing word Typo
* Fixed Punctuation: Two commas
* Fixed Punctuation: No Space between XLM-R and is
* Fixed Punctuation: No Space between [~accelerate.Accelerator.backward] and method
* Added backticks to display model.fit() in codeblock
* Added backticks to display openai-community/gpt2 in codeblock
* Fixed Minor Typo: will to with
* Fixed Minor Typo: is to are
* Fixed Minor Typo: in to on
* Fixed Minor Typo: inhibits to exhibits
* Fixed Minor Typo: they need to it needs
* Fixed Minor Typo: cast the load the checkpoints To load the checkpoints
* Fixed Inconsistent Class Name Typo: TFCamembertForCasualLM to TFCamembertForCausalLM
* Fixed typo in attribute name: outputs.last_hidden_states to outputs.last_hidden_state
* Added missing verbosity level: fatal
* Fixed Minor Typo: take To takes
* Fixed Minor Typo: heuristic To heuristics
* Fixed Minor Typo: setting To settings
* Fixed Minor Typo: Content To Contents
* Fixed Minor Typo: millions To million
* Fixed Minor Typo: difference To differences
* Fixed Minor Typo: while extract To which extracts
* Fixed Minor Typo: Hereby To Here
* Fixed Minor Typo: addition To additional
* Fixed Minor Typo: supports To supported
* Fixed Minor Typo: so that benchmark results TO as a consequence, benchmark
* Fixed Minor Typo: a To an
* Fixed Minor Typo: a To an
* Fixed Minor Typo: Chain-of-though To Chain-of-thought
* use gguf internal dequantize
* add Q5_0 test
* add iq1 test
* add remained test
* remove duplicated test
* update docs
* add gguf version limit
* make style
* update gguf import catch
* revert vocab_size patch
* make style
* use GGUF_MIN_VERSION everywhere
* Adding SDPA support for RoBERTa-based models
* add not is_cross_attention
* fix copies
* fix test
* add minimal test for camembert and xlm_roberta as their test class does not inherit from ModelTesterMixin
* address some review comments
* use copied from
* style
* consistency
* fix lists
---------
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add Blip2ForImageTextRetrieval
* use one line and remove unnecessary space in tests
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* use value from the config, rather than hardcoded
* change order of params in Blip2QFormerModel.forward
* update docstring
* fix style
* update test_inference_opt
* move embeddings out of Blip2QFormerModel
* remove from_vision_qformer_configs
* remove autocast float16 in Blip2QFormerModel
* rename fiels into vision_projection,text_projection,use_image_text_matching_head
* use CLIPOutput for Blip2ImageTextMatchingModelOutput
* remove past_key_values_length from Blip2TextEmbeddings
* fix small typo in the CLIPOutput docstring
* add Blip2ForImageTextRetrieval to Zero Shot Image Classification mapping
* update docstring and add require_torch_fp16
* rollback test_inference_opt
* use use_image_text_matching_head=True in convert
* skip test_model_get_set_embeddings
* fix create_rename_keys error on new itm fields
* revert to do scale after dot product between "query" and "key"
* fix ValueError on convert script for blip2-opt-2.7b
* update org of paths to Salesforce
* add is_pipeline_test_to_skip for VisualQuestionAnsweringPipelineTests
* [run_slow] blip_2
* removed Blip2ForImageTextRetrieval from IGNORE_NON_AUTO_CONFIGURED
* fix docstring of Blip2ImageTextMatchingModelOutput
* [run_slow] blip_2
* fix multi-gpu tests
* [run_slow] blip_2
* [run_slow] blip_2
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Very small change to one of the parameters
np.random.randint second parameter is not included in the possible options. Therefore, we want the upper range to be 2, so that we have some 1 labels in our classification as well.
* Add changes for uroman package to handle non-Roman characters
* Update docs for uroman changes
* Modifying error message to warning, for backward compatibility
* Update instruction for user to install uroman
* Update docs for uroman python version dependency and backward compatibility
* Update warning message for python version compatibility with uroman
* Refine docs
* Fix: fix all model_type of Llava-Next-Video to llava_next_video
* Fix doc for llava_next_video
* * Fix formatting issues
* Change llava-next-video.md file name into llava_next_video.md to make it compatible with implementation
* Fix docs TOC for llava-next-video
* more precise name
* better docstrings
* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update the Kubernetes CPU training example
* Add namespace arg
Signed-off-by: Dina Suehiro Jones <dina.s.jones@intel.com>
---------
Signed-off-by: Dina Suehiro Jones <dina.s.jones@intel.com>
* Add TorchAOHfQuantizer
Summary:
Enable loading torchao quantized model in huggingface.
Test Plan:
local test
Reviewers:
Subscribers:
Tasks:
Tags:
* Fix a few issues
* style
* Added tests and addressed some comments about dtype conversion
* fix torch_dtype warning message
* fix tests
* style
* TorchAOConfig -> TorchAoConfig
* enable offload + fix memory with multi-gpu
* update torchao version requirement to 0.4.0
* better comments
* add torch.compile to torchao README, add perf number link
---------
Co-authored-by: Marc Sun <marc@huggingface.co>
* Rename "Templates for Chat Models" doc to "Chat Templates"
* Small formatting fix
* Small formatting fix
* Small formatting fix
* Cleanup tool calling docs as well
* Remove unneeded 'revision'
* Move tip to below main code example
* Little bonus section on template editing
* add new model like
* draft cuda forward - mismatched keys (sharding on conv1)
* match keys successfully
* fix split
* get generation/forward running (wrong gens, norm?)
* :update
* some refactoring
* fixes
* works up until copy to cache
* fix
* update
* NON WORKING VERSION
* version that work?
* nit
* fix config
* fix conversion script
* working cuda forward
* nit
* update
* simplifcation
* make mamba slow simple work
* no einops
* todo
* fix style
* no einops
* update fix no einsum
* nit
* remove einops
* bug: scan_output differs strongly
* add rms norm option
* fix fast + slow generation with and w/o cache ✔️
* draft integration tests
* remove a big chunk of the einsum
* fix slow, fast generations, without any einsum
* fix copies
* fix structure
* fix up modeling and tests
* fix tests
* clamping is indeed worse
* recover mamba2 cache test
* fix copies
* no cache position (yet)
* fix tf tests
* fix matmul for generate
* fixup
* skip cache tests for now
* [run-slow]mamba2
* tune out hidden states for padding
* test batched generation
* propagate attention mask changes
* fix past length
* fix integration test
* style
* address comments
* update readme
* add mamba2 version check
* fix tests
* [run-slow]mamba2
* skip edge tests
* [run-slow]mamba2
* last fixup
* [run-slow]mamba2
* update README
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
* Initial implementation of OffloadedCache
* enable usage via cache_implementation
* Address feedback, add tests, remove legacy methods.
* Remove flash-attn, discover synchronization bugs, fix bugs
* Prevent usage in CPU only mode
* Add a section about offloaded KV cache to the docs
* Fix typos in docs
* Clarifications and better explanation of streams
* mvp
* added test (a few models need fixes)
* fix a few test cases
* test nits
* harder test 😈
* revert changes in stablelm
* test with improved condition
* add todo
* tmp commit
* merged with main
* nits
* add todo
* final corrections
* add docs for generation compilation
* docs nits
* add tip
* PR suggestions
* add more details to the compilation docs
* fix cache positions
* cache is now init in generate; update docs
* tag test as flaky
* docs
* post rebase make fixup and other nits
* remove unintended changes
* whisper (encoder-decoder) not supported
* move token default updates to ; add tests for token defaults
* push changes
* manual rebase
* chameleon doesn't support this
* fix test_static_cache_mha_mqa_gqa (broken in another PR)
* docs: dynamic is better with end-to-end compilation
* No more default chat templates
* Add the template to the GPT-SW3 tests since it's not available by default now
* Fix GPT2 test
* Fix Bloom test
* Fix Bloom test
* Remove default templates again
* add DataCollatorBatchFlattening
* Update data_collator.py
* change name
* new FA2 flow if position_ids is provided
* add comments
* minor fix
* minor fix data collator
* add test cases for models
* add test case for data collator
* remove extra code
* formating for ruff check and check_repo.py
* ruff format
ruff format tests src utils
* custom_init_isort.py
* Add llama3-llava-next-8b to llava_next conversion script
Adds support for the lmms-lab/llama3-llava-next-8b model to the
convert_llava_next_weights_to_hf.py script, along with an example
prompt generated from the llava_llama_3 conv_template in the LLaVA-NeXT
repo.
* Exclude <|begin_of_text|> from prompt example
This token gets added automatically, so it should not be included in the
prompt example.
* Add llava-next-72b and llava-next-110b
Adds the Qwen-based LLaVA-Next models to the conversion script, along
with changes to load the models on multiple GPUs for inference.
* Add llama3 and qwen prompt formats to docs
* Chat prompt and padding side left for llama3 batched
* update
* Update src/transformers/models/llava_next/convert_llava_next_weights_to_hf.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/llava_next/convert_llava_next_weights_to_hf.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* remove code
* better naming
---------
Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: Raushan Turganbay <raushan.turganbay@alumni.nu.edu.kz>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* minor edits and clarifications
* address comment
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 1,100%!
* Clean
* Don't touch DS
* Experiment with dtype allocation
* skip test_load_save_without_tied_weights test
* A little faster
* Include proper upscaling?
* Fixup tests
* Potentially skip?
* Let's see if this fixes git history
* Maintain new dtype
* Fin
* Rm hook idea for now
* New approach, see what breaks
* stage
* Clean
* Stash
* Should be fin now, just need to mark failing models
* Clean up
* Simplify
* Deal with weird models
* Enc/Dec
* Skip w/ reason
* Adjust test
* Fix test
* one more test
* Keep experimenting
* Fix ref
* TO REMOVE: testing feedback CI
* Right push
* Update tests/utils/test_modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* disable
* Add new func
* Test nits from Amy
* Update src/transformers/modeling_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Adjust comment
* Adjust comment on skip
* make private
* Fin
* Should be a not flag
* Clarify and rename test
---------
Co-authored-by: Marc Sun <marc@huggingface.co>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* cast image features to model.dtype where needed to support FP16 or other precision in pipelines
* Update src/transformers/pipelines/image_feature_extraction.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Use .to instead
* Add FP16 pipeline support for zeroshot audio classification
* Remove unused torch imports
* Add docs on FP16 pipeline
* Remove unused import
* Add FP16 tests to pipeline mixin
* Add fp16 placeholder for mask_generation pipeline test
* Add FP16 tests for all pipelines
* Fix formatting
* Remove torch_dtype arg from is_pipeline_test_to_skip*
* Fix format
* trigger ci
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Repeating an important warning in the chat template docs
* Update docs/source/en/chat_templating.md
Co-authored-by: Lysandre Debut <hi@lysand.re>
* Reword for clarity
* Reword for clarity
---------
Co-authored-by: Lysandre Debut <hi@lysand.re>
* Add siglip loss function
* Update docs
* Enable training tests
[experimental] enable GC training tests as it has worked for my own data
* Remove test_training* overrides to enable training tests
[run_slow] siglip
* Skip training tests for Siglip text model and ImageClassificationModel
[run_slow] siglip
* Skip GC training tests for SiglipForImageClassification
* Explicitly skip training tests for SiglipVisionModel
Add skip reason for training tests for SiglipTextModel
* Remove copied from to fix CI
* Update CometCallback to allow reusing of the running experiment
* Fixups
* Remove useless TODO
* Add checks for minimum version of the Comet SDK
* Fix documentation and links.
Also simplify how the Comet Experiment name is passed
* Add torch_empty_cache_steps to TrainingArguments
* Fix formatting
* Add torch_empty_cache_steps to docs on single gpu training
* Remove check for torch_empty_cache_steps <= max_steps
* Captalize Tip
* Be device agnostic
* Fix linting
* Fix documentation for Gemma2.
Model sizes and Blog post URL are wrong in the documentation.
* Update docs/source/en/model_doc/gemma2.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* squash into single commit
* run diff once more
* docstring
* tests
* minor chnages and ready to go
* Update src/transformers/models/llava_next_video/processing_llava_next_video.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/vipllava/test_modeling_vipllava.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* [run-slow] llava-next-video
* [run-slow] llava-next-video
* [run-slow] llava_next_video
* fix two tests
* fix slow tests
* remove logit checks due to numeric errors
* run test once more
* [run-slow] llava_next_video
* final try to pass the test
* [run-slow] llava_next_video
* [run-slow] llava_next_video
* [run-slow] llava_next_video
* style
* fix
* style
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* starting support for sdpa in `gptneox` models
* small comment on tests
* fix dropout
* documentation and style
* clarify concrete paths for reference
* generalise attn projections and rope application
added head mask check to sdpa mask creation
handle sdpa memory backend bug via own version flag
* update docs and style
* move dtype casting outside of general attn_projection_and_rope function
fix flash_attn_2 stuff
* more generic attn warning if output_attns or head_mask
* simplify head mask check by moving head mask creation to a later point
* remove copied llama artifact
* remove padding_mask from attention function signature
* removing unnecessary comments, only "save" attn implementation once
* [run_slow] gpt_neox
* Update perf_train_gpu_many.md
* Update docs/source/en/perf_train_gpu_many.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/perf_train_gpu_many.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update chat template docs
* Minor bug in the version check
* Update docs/source/en/chat_templating.md
Co-authored-by: Joshua Lochner <admin@xenova.com>
* Update docs/source/en/chat_templating.md
Co-authored-by: Joshua Lochner <admin@xenova.com>
* Update docs/source/en/chat_templating.md
Co-authored-by: Joshua Lochner <admin@xenova.com>
* Replace backticks with bolding because the doc builder was trying to parse them
* Replace backticks with bolding because the doc builder was trying to parse them
* Replace backticks with bolding because the doc builder was trying to parse them
* More cleanups to avoid upsetting the doc builder
* Add one more tip at the end
---------
Co-authored-by: Joshua Lochner <admin@xenova.com>
* Draft fast image processors
* Draft working fast version
* py3.8 compatible cache
* Enable loading fast image processors through auto
* Tidy up; rescale behaviour based on input type
* Enable tests for fast image processors
* Smarter rescaling
* Don't default to Fast
* Safer imports
* Add necessary Pillow requirement
* Woops
* Add AutoImageProcessor test
* Fix up
* Fix test for imagegpt
* Fix test
* Review comments
* Add warning for TF and JAX input types
* Rearrange
* Return transforms
* NumpyToTensor transformation
* Rebase - include changes from upstream in ImageProcessingMixin
* Safe typing
* Fix up
* convert mean/std to tesnor to rescale
* Don't store transforms in state
* Fix up
* Update src/transformers/image_processing_utils_fast.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Warn if fast image processor available
* Update src/transformers/models/vit/image_processing_vit_fast.py
* Transpose incoming numpy images to be in CHW format
* Update mapping names based on packages, auto set fast to None
* Fix up
* Fix
* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test
* Update src/transformers/models/vit/image_processing_vit_fast.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Add equivalence and speed tests
* Fix up
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* First draft, still missing automatic function conversion
* First draft of the automatic schema generator
* Lots of small fixes
* the walrus has betrayed me
* please stop committing your debug breakpoints
* Lots of cleanup and edge cases, looking better now
* Comments and bugfixes for the type hint parser
* More cleanup
* Add tests, update schema generator
* Update tests, proper handling of return values
* Small docstring change
* More doc updates
* More doc updates
* Add json_schema decorator
* Clean up the TODOs and finish the docs
* self.maxDiff = None to see the whole diff for the nested list test
* add import for add_json_schema
* Quick test fix
* Fix something that was bugging me in the chat template docstring
* Less "anyOf" when unnecessary
* Support return types for the templates that need them
* Proper return type tests
* Switch to Google format docstrings
* Update chat templating docs to match new format
* Stop putting the return type in with the other parameters
* Add Tuple support
* No more decorator - we just do it implicitly!
* Add enum support to get_json_schema
* Update docstring
* Add copyright header
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update docs/source/en/chat_templating.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/utils/chat_template_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/utils/chat_template_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add copyright header
* make fixup
* Fix indentation
* Reformat chat_template_utils
* Correct return value
* Make regexes module-level
* Support more complex, multi-line arg docstrings
* Update error message for ...
* Update ruff
* Add document type validation
* Refactor docs
* Refactor docs
* Refactor docs
* Clean up Tuple error
* Add an extra test for very complex defs and docstrings and clean everything up for it
* Document enum block
* Quick test fixes
* Stop supporting type hints in docstring to fix bugs and simplify the regex
* Update docs for the regex change
* Clean up enum regex
* Wrap functions in {"type": "function", "function": ...}
* Update src/transformers/utils/chat_template_utils.py
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
* Temporary tool calling commit
* Add type hints to chat template utils, partially update docs (incomplete!)
* Code cleanup based on @molbap's suggestion
* Add comments to explain regexes
* Fix up type parsing for unions and lists
* Add custom exception types and adjust tests to look for them
* Update docs with a demo!
* Docs cleanup
* Pass content as string
* Update tool call formatting
* Update docs with new function format
* Update docs
* Update docs with a second tool to show the model choosing correctly
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
* Remove ConversationalPipeline and Conversation object, as they have been deprecated for some time and are due for removal
* Update not-doctested.txt
* Fix JA and ZH docs
* Fix JA and ZH docs some more
* Fix JA and ZH docs some more
* add tokenizer_summary to es/_toctree.yml
* add tokenizer_summary to es/
* fix link to Transformes XL in en/
* translate until Subword tokenization section
* fix GPT link in en/
* fix other GPT link in en/
* fix typo in en/
* translate the doc
* run make fixup
* Remove .md in Transformer XL link
* fix some link issues in es/
* fix typo
`mask` variable is not defined. probably a writing mistake. it should be `segmentation_map`. `segmentation_map` should be a `1` channel image rather than `RGB`.
[on a different note, the `mask_url` is the same as `raw_image`. could provide a better example.
* Fix has_file in offline mode
* harmonize env variable for offline mode
* Switch to HF_HUB_OFFLINE
* fix test
* revert test_offline to test TRANSFORMERS_OFFLINE
* Add new offline test
* merge conflicts
* docs
* Change in quantization docs
* Update overview.md
* Update docs/source/en/quantization/overview.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* clean-up
* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixup
* Update tests/quantization/quanto_integration/test_quanto.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* more suggestions
* mapping if torch available
* run tests & add 'support_quantized' flag
* fix jamba test
* revert, will be fixed by another PR
* codestyle
* HQQ and versatile cache classes
* final update
* typo
* make tests happy
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* add model_memory_anatomy to es/_toctree.yml
* copy model_memory_anatomy.md to es/
* translate first section
* translate doc
* chage forward activations
* fix sentence and and link to Trainer
* fix Trainer link
* Add MistralForTokenClassification
* Add tests and docs
* Add token classification for Mixtral and Qwen2
* Save llma for token classification draft
* Add token classification support for Llama, Gemma, Persimmon, StableLm and StarCoder2
* Formatting
* Add token classification support for Qwen2Moe model
* Add dropout layer to each ForTokenClassification model
* Add copied from in tests
* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Propagate suggested changes
* Style
---------
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* add method
* change method name
* more comments
* Apply suggestions from code review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fixup
* add docstrings and fix comment
* warn users on the de-quantized dtype
* Update src/transformers/quantizers/base.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/integrations/bitsandbytes.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* final suggestion - use private method
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Initial commit
* Just a copy of modeling_idefics.py that will be ported to TF
* - Prepend TF to the name of all classes
- Convert pytorch ops to TF (not all operations are converted yet)
* Add TF imports
* Add autotranslated files
* Add TF classes to model_tf_auto.py
* Add the TF classes in model_doc
* include auto-translated code
* Adopted from auto-translated version
* Add a forgotten super().build
* Add test code for TF version.
* Fix indentation and load pytorch weights for now
* Some fixes. Many tests are still failing but some are passing now.
- I have added TODO's for some of the hacks I made to unblock me
and I will address them soon
- I have the processing_idefics.py hacked in my view to support TF temporarily
* Add ALL_LAYERNORM_LAYERS to match pytorch
* Revert "Add ALL_LAYERNORM_LAYERS to match pytorch"
This reverts commit 7e0a35119b4d7a6284d04d8c543fba1b29e573c9 as it
is not needed in the tf implementation.
* Fix freeze_relevant_params()
* Some more fixes
* Fix test_attention_outputs
* Add tf stuff to processing_idefics.py
processing_idefics.py supports both pytorch and tf now.
test_processor_idefics.py for pytorch is passing, so i didn't break anything
but still some issues with tf. I also need to add tf tests in
test_processor_idefics.py.
* Pass return_tensors to image processing code and fix test
* Pass return_tensors to the image processor __init__
* Fix several test cases
- Make input to some of the forward pass of type `TFModelInputType`
- Decorate main layer forward pass with `@unpack_inputs`
- Decorate main layer with `@keras_serializable`
- Pass `inputs` to TFIdeficsModel
* Some more fixes forgotten in last commit
* Fix processing code and vision_tf.py
* Fix perceiver bug
* Import from
* Auto-add build() methods + style pass
* Fix build() errors due to `None` being passed as shape to some layers
* Change name in TFIdeficsForVisionText2Text to attribute in IdeficsForVisionText2Text
* Fix pytorch weights load for tf2
There were a lot of `name=` missing in weight initialization code.
* Attempt to fix CI
* Add back accidently removed line
* Remove torch-specific stuff from the TF test file
* make fix-copies, make style, remove autotranslated files
* Fixes to imports/docstrings
* Let's try the from future import in desperation
* Fix the core random_attention_mask fn to match the torch/flax behaviour
* Clean random_attention_mask up correctly
* Remove torch-only test
* Fix loss shape, couple of nits
* make style
* Don't test for OOB embeddings because IDEFICS uses those deliberately
* Fix loss computation to handle masking
* Fix test failures when flattening
* Fix some test failures
- Add cross attention gate which was missing and wasn't being passed arround
- Fix overwriting of image_attention_mask due to hack I had for dummy inputs
* Add a proper stateless scaled_dot_product_attention
* make style
* Adding missing attribute from the PyTorch version
* Small cleanups to decoupledlinearlayer in case that helps
* Pass epsilon to LayerNormalization
* Attemp to fix pytorch weight cross-loading for TFIdeficsEmbedding
* Fix a bug in TFIdeficsGatedCrossAttentionLayer
* Patching up build() methods
* Constant self.inv_freq
* Constant self.inv_freq
* First working version
The TF implementation works now, there was a bug in the TFIdeficsDecoupledLinear
where the weights were mis-intialized (in_features,out_features)
when it should be: (out_features, in_features)
I have tested this so far with tiny-random and idefics-9b-instruct
and gives correct output.
I also dumped the final outputs for both pytorch and TF
and they are identical.
* Fix some test failures
* remove print statement
* Fix return_tensors
* Fix CI test failure check_code_quality
* Attempt to fix CI failures by running `make fixup`
The hardcoded IDs in test_modeling_tf_idefics.py are for the integration
test and makes that file unreadable and should probably be moved to a seperate file.
* Attempt to fix tests_pr_documentation_tests
* Fix a test failure in test_image_processing_idefics.py
* Fix test test_pt_tf_model_equivalence
* Fix a few failures
* Tiny fix
* Some minor fixes
* Remove a duplicate test
* Override a few test failures for IDEFICS
- `test_keras_save_load` is passing now
- `test_compile_tf_model` is still failing
* Fix processing_idefics.py after rebase
* Guard import keras with is_tf_available
* fix check code quality
* fix check code quality
* Minor fixes
* Skip test_save_load temporarily
This test passed on my local box but fails on the CI, skipping
for now to see if there are other remaining failures on the CI.
* Run `ruff format tests src utils`
* Fix last failing test, `test_compile_tf_model`
* Add fixes for vision_tf.py
I forgot to add this file in last commit.
* Minor fixes
* Replace "<<<" with "<<" for doc tests
IDEFICS-9B is too big for doctest runner, so don't run it there
* Make code more readable
* Fix bug after code review
I added a layer_norm_eps to IdeficsConfig but I don't even need it
since the vision config has a layer_norm_eps.
* Fix after code review
Use original code tokenizer.convert_tokens_to_ids
* Keep PyTorch as the default return_tensors
* Fixes to modeling_tf after code review
* Fixes from code review
- Remove all references of `TF_IDEFICS_PRETRAINED_MODEL_ARCHIVE_LIST`
- Pass 1e-5 to LayerNormalization in perceiver
* Run ruff
* Undo a change
* Refactor processing code after Matt's suggestion
* Remove TODO's that aren't needed anymore
* For pytorch, Use original pytorch processing code from main
Since this PR is a TF port it shouldn't make any modifications
to pytorch IDEFICS code. This changes undo's the pytorch processing
modifications I made and uses original code from main.
* Update tests/models/idefics/test_modeling_idefics.py
* Update tests/models/idefics/test_modeling_tf_idefics.py
* Add missing imports for is_pt_tf_cross_test
* [DO NOT MERGE]: This is a commit for debugging and will be reverted
The cross test `test_pt_tf_model_equivalence` passes locally but
fails when running on the CI. This commit is to help debug that
and will be reverted.
* Revert "[DO NOT MERGE]: This is a commit for debugging and will be reverted"
This reverts commit 8f0d709ec5bd46685fb0b4259d914ffee794875b.
* [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted
* [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted
* Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted"
This reverts commit 998cc38b8c3d313bf5e5eb55a7f5b7b881897b89.
* Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted"
This reverts commit 1c695ac4219c4ae4d39b330b01744dc27deb7dd4.
* Don't skip test_save_load
IIRC test_save_load was also failing on the CI but not on my local
box, it might be easier to debug that on the CI first than the cross tests
* Debugging commit, will be reverted
* Revert "Debugging commit, will be reverted"
This reverts commit 8eafc8e41e20c4e95a3a90834f06a6e9f445e2d5.
* Override `test_save_load` and push model to save
Maybe this will help me repro this weird bug
* pass my repo_id
* add endpoint
* Pass a temp (write) token just for this CI
* Undo last few commits, still pushing to hub for model debugging
The issue seems to be with save_pretrained(), when I looked at the model saved
from the CI test failure it is basically empty and has no weights.
`self.save_weights(..)` seems to be failing in save_pretrained but needs
more debugging
* Add logging to modeling tf utils, will be reverted just for debugging
* Debugging, will revert
* Revert "Debugging, will revert"
This reverts commit 9d0d3075fb7c82d8cde3a5c76bc8f3876c5c55d3.
* Revert "Add logging to modeling tf utils, will be reverted just for debugging"
This reverts commit 774b6b7b1c17b3ce5d7634ade768f2f686cee617.
* Remove `test_save_load`
The CI failures are gone after my latest rebase, no idea why
but I was still saving the model to my hub on HF and the tf_model.h5
file now has everything.
* Run make fix-copies
* Run ruff format tests src utils
* Debugging commit, will be reverted
* Run ruff, also trigger CI run
* Run ruff again
* Undo debugging commit
---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Create CodeAgent and ReactAgent
* Fix formatting errors
* Update documentation for agents
* Add custom errors, improve logging
* Support variable usage in ReactAgent
* add messages
* Add message passing format
* Create React Code Agent
* Update
* Refactoring
* Fix errors
* Improve python interpreter
* Only non-tensor inputs should be sent to device
* Calculator tool slight refactor
* Improve docstrings
* Refactor
* Fix tests
* Fix more tests
* Fix even more tests
* Fix tests by replacing output and input types
* Fix operand type issue
* two small fixes
* EM TTS
* Fix agent running type errors
* Change text to speech tests to allow changed outputs
* Update doc with new agent types
* Improve code interpreter
* If max iterations reached, provide a real answer instead of an error
* Add edge case in interpreter
* Add safe imports to the interpreter
* Interpreter tweaks: tuples and listcomp
* Make style
* Make quality
* Add dictcomp to interpreter
* Rename ReactJSONAgent to ReactJsonAgent
* Misc changes
* ToolCollection
* Rename agent's logger to self.logger
* Add while loops to interpreter
* Update doc with new tools. still need to mention collections
* Add collections to the doc
* Small fixes on logs and interpretor
* Fix toolbox return type
* Docs + fixup
* Skip doctests
* Correct prompts with improved examples and formatting
* Update prompt
* Remove outdated docs
* Change agent to accept Toolbox object for tools
* Remove calculator tool
* Propagate removal of calculator in doc
* Fix 2 failing workflows
* Simplify additional argument passing
* AgentType audio
* Minor changes: function name, types
* Remove calculator tests
* Fix test
* Fix torch requirement
* Fix final answer tests
* Style fixes
* Fix tests
* Update docstrings with calculator removal
* Small type hint fixes
* Update tests/agents/test_translation.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/agents/test_python_interpreter.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/default_tools.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/tools.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/agents/test_agents.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/bert/configuration_bert.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/tools.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/speech_to_text.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/agents/test_speech_to_text.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/agents/test_tools_common.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* pygments
* Answer comments
* Cleaning up
* Simplifying init for all agents
* Improving prompts and making code nicer
* Style fixes
* Add multiple comparator test in interpreter
* Style fixes
* Improve BERT example in documentation
* Add examples to doc
* Fix python interpreter quality
* Logging improvements
* Change test flag to agents
* Quality fix
* Add example for HfEngine
* Improve conversation example for HfEngine
* typo fix
* Verify doc
* Update docs/source/en/agents.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/agents.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/prompts.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/agents/python_interpreter.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update docs/source/en/agents.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Fix style issues
* local s2t tool
---------
Co-authored-by: Cyril Kondratenko <kkn1993@gmail.com>
Co-authored-by: Lysandre <lysandre@huggingface.co>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Adding SDPA support for BERT
* Using the proper input name for testing model input in inference()
* Adding documentation for SDPA in BERT model page
* Use the stable link for the documentation
* Adding a gate to only call .contiguous() for torch < 2.2.0
* Additions and fixes to the documentation
* Minor updates to documentation
* Adding extra requirements needed for the contiguous() bug
* Adding "Adapted from" in plcae of the "Copied from"
* Add benchmark speedup tables to the documentation
* Minor fixes to the documentation
* Use ClapText as a replacemenet for Bert in the Copied-From
* Some more fixes for the fix-copies references
* Overriding the test_eager_matches_sdpa_generate in bert tests to not load with low_cpu_mem_usage
[test all]
* Undo changes to separate test
* Refactored SDPA self attention code for KV projections
* Change use_sdpa to attn_implementation
* Fix test_sdpa_can_dispatch_on_flash by preparing input (required for MultipleChoice models)
* Draft tutorial for talking to chat models
* Reformat lists and text snippets
* Cleanups and clarifications
* Finish up remaining TODOs
* Correct section link
* Small fix
* Add proper quantization examples
* Add proper quantization examples
* Add proper quantization examples
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/_toctree.yml
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/conversations.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Fix Text Generation Pipeline link and add a ref to the LLM inference guide
* intelligent -> capable
* Small intro cleanup
* Small text cleanup
* Small text cleanup
* Clarification about system message
* Clarification about system message
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* chore(root): Initial commit of Phi-3 files.
* fix(root): Fixes Phi-3 missing on readme.
* fix(root): Ensures files are consistent.
* fix(phi3): Fixes unit tests.
* fix(tests): Fixes style of phi-3 test file.
* chore(tests): Adds integration tests for Phi-3.
* fix(phi3): Removes additional flash-attention usage, .e.g, swiglu and rmsnorm.
* fix(phi3): Fixes incorrect docstrings.
* fix(phi3): Fixes docstring typos.
* fix(phi3): Adds support for Su and Yarn embeddings.
* fix(phi3): Improves according first batch of reviews.
* fix(phi3): Uses up_states instead of y in Phi3MLP.
* fix(phi3): Uses gemma rotary embedding to support torch.compile.
* fix(phi3): Improves how rotary embedding classes are defined.
* fix(phi3): Fixes inv_freq not being re-computed for extended RoPE.
* fix(phi3): Adds last suggestions to modeling file.
* fix(phi3): Splits inv_freq calculation in two lines.
* [FEAT]: EETQ quantizer support
* Update quantization.md
* Update docs/source/en/main_classes/quantization.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update docs/source/en/quantization.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update docs/source/en/quantization.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/integrations/__init__.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/integrations/__init__.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/integrations/eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/integrations/eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/integrations/eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update tests/quantization/eetq_integration/test_eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/quantizers/auto.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/quantizers/auto.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/quantizers/auto.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/quantizers/quantizer_eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update tests/quantization/eetq_integration/test_eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update src/transformers/quantizers/quantizer_eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update tests/quantization/eetq_integration/test_eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update tests/quantization/eetq_integration/test_eetq.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* [FEAT]: EETQ quantizer support
* [FEAT]: EETQ quantizer support
* remove whitespaces
* update quantization.md
* style
* Update docs/source/en/quantization.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* add copyright
* Update quantization.md
* Update docs/source/en/quantization.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update docs/source/en/quantization.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Address the comments by amyeroberts
* style
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Marc Sun <marc@huggingface.co>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Duplicate swiftformer
* Convert SwiftFormerPatchEmbedding
* Convert SwiftFormerEmbeddings
* Convert TFSwiftFormerMlp
* Convert TFSwiftFormerConvEncoder
* Convert TFSwiftFormerLocalRepresentation
* convert TFSwiftFormerEncoderBlock
* Convert SwiftFormerStage
* Convert SwiftFormerEncoder
* Add TFSWiftFormerPreTrainedModel
* Convert SwiftFormerForImageClassification
* Add kwargs and start drop path
* Fix syntax
* Change Model class name
* Add TFSwiftFormer to __init__
* Duplicate test_modeling_swiftformer
* First test conversions
* Change require_torch to require_tf
* Add exports to swiftformer __init__
* Add TFSwiftFormerModel wrapper
* Fix __init__ and run black
* Remove docstring from MainLayer, fix padding
* Use keras.layers.Activation on keras.Sequential
* Fix swiftformer exports
* Fix activation layer from config
* Remove post_inits
* Use tf.keras.layers.ZeroPadding2D
* Convert torch normalize
* Change tf test input shape
* Fix softmax and reduce_sum
* Convert expand_dims and repeat
* Add missing reshape and tranpose
* Simplify TFSwiftFormerEncoderBlock.call
* Fix mismatch in patch embeddings
* Fix expected output shape to match channels last
* Fix swiftformer typo
* Disable test_onnx
* Fix TFSwiftFormerForImageClassification call
* Add unpack inputs
* Convert flatten(2).mean(-1)
* Change vision dummy inputs (to be reviewed)
* Change test_forward_signature to use .call
* Fix @unpack_inputs
* Set return_tensors="tf" and rename class
* Rename wrongly named patch_embeddings layer
* Add serving_output and change dummy_input shape
* Make dimensions BCHW and transpose inside embedding layer
* Change SwiftFormerEncoderBlock
* Fix ruff problems
* Add image size to swiftformer config
* Change tranpose to MainLayer and use -1 for reshape
* Remove serving_outputs and dummy_inputs
* Remove test_initialization test from tf model
* Make Sequential component a separate layer
* Fix layers' names
* Tranpose encoder outputs
* Fix tests and check if hidden states is not None
* Fix TFSwiftFormerForImageClassification
* Run make fixup
* Run make fix-copies
* Update modeling_tf_auto
* Update docs
* Fix modeling auto mapping
* Update modelint_tf_swiftformer docs
* Fill image_size doc and type
* Add reduction=None to loss computation
* Update docs
* make style
* Debug: Delete the tip to see if that changes anything
* Re-add tip
* Remove add_code_sample_docstrings
* Remove unused import
* Get the debug to actually tell us the problem it has with the docs
* Try a substitution to match the PyTorch file?
* Add swiftformer to ignore list
* Add build() methods
* Update copyright year
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Remove FIXME comment
* Remove from_pt
* Update copyright year
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Rename one-letter variables
* Remove FIXMEs related to momentum
* Remove old TODO comment
* Remove outstanding FIXME comments
* Get dropout rate from config
* Add specific dropout config for MLP
* Add convencoder dropout to config
* Pass config to SwiftFormerDropPath layer
* Fix drop_path variable name and add Adapted from comment
* Run ruff
* Removed copied from comment
* Run fix copies
* Change drop_path to identity to match pt
* Cleanup build() methods and move to new keras imports
* Update docs/source/en/model_doc/swiftformer.md
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Raise error if drop_path_rate > 0.0
* Apply suggestions from code review
Replace (self.dim), with self.dim,
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Remove drop_path function
* Add training to TFSwiftFormerEncoder
* Set self.built = True last
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Should have been added to previous commit
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>
* Change default_feature_extractor to default_image_processor
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Import Keras from modeling_tf_utils
* Remove relative import
* Run ruff --fix
* Move import keras to tf_available
* Add copied from comment to test_forward_signature
* Reduce batch size and num_labels
* Extract loss logic to hf_compute_loss
* Run ruff format
---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* initial commit, remove warnings on default chat templates
* stash commit
* Raise a much sterner warning for default chat templates, and prepare for depreciation
* Update the docs
* wip
* fix __init__.py
* add docs
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* address comments 1
* work on make fixup
* pass configs down
* add sdpa attention
* remove DbrxBlock
* add to configuration_auto
* docstring now passes formatting test
* fix style
* update READMEs
* add dbrx to modeling_auto
* make fix-copies generated this
* add DBRX_PRETRAINED_CONFIG_ARCHIVE_MAP
* config docstring passes formatting test
* rename moe_loss_weight to router_aux_loss_coef
* add to flash-attn documentation
* fix model-path in tests
* Explicitly make `"suli"` the default `ffn_act_fn`
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* default to using router_aux_loss_coef over ffn_config[moe_loss_weight]
* fix _flash_attn_uses_top_left_mask and is_causal
* fix tests path
* don't use token type IDs
* follow Llama and remove token_type_ids from test
* init ConfigTester differently so tests pass
* remove multiple choice test
* remove question + answer test
* remove sequence classification test
* remove token classification test
* copy Llama tests and remove token_type_ids from test inputs
* do not test pruning or headmasking; style code
* add _tied_weights_keys parameter to pass test
* add type hints
* fix type check
* update config tester
* remove masked_lm test
* remove encoder tests
* initialize DbrxModelTester with correct params
* style
* torch_dtype does not rely on torch
* run make fixup, fix-copies
* use https://huggingface.co/v2ray/dbrx-base-fixed/blob/main/modeling_dbrx.py
* add copyright info
* fix imports and DbrxRotaryEmbedding
* update DbrxModel docstring
* use copies
* change model path in docstring
* use config in DbrxFFN
* fix flashattention2, sdpaattention
* input config to DbrXAttention, DbrxNormAttentionNorm
* more fixes
* fix
* fix again!
* add informative comment
* fix ruff?
* remove print statement + style
* change doc-test
* fix doc-test
* fix docstring
* delete commented out text
* make defaults match dbrx-instruct
* replace `router_aux_loss_coef` with `moe_loss_weight`
* is_decoder=True
* remove is_decoder from configtester
* implement sdpa properly
* make is_decoder pass tests
* start on the GenerationTesterMixin tests
* add dbrx to sdpa documentation
* skip weight typing test
* style
* initialize smaller model
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Add DBRX to toctree
* skip test_new_cache_format
* make config defaults smaller again
* add pad_token_id
* remove pad_token_id from config
* Remove all references to DBRX_PRETRAINED_CONFIG_ARCHIVE_MAP
* Update src/transformers/models/dbrx/__init__.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/dbrx/modeling_dbrx.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update docs/source/en/model_doc/dbrx.md
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Update src/transformers/models/dbrx/configuration_dbrx.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update docs/source/en/model_doc/dbrx.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix typo
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* update docs, fix configuration_auto.py
* address pr comments
* remove is_decoder flag
* slice
* fix requires grad
* remove grad
* disconnect differently
* remove grad
* enable grads
* patch
* detach expert
* nissan al ghaib
* Update modeling_dbrx.py
* Update src/transformers/models/dbrx/modeling_dbrx.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* replace "Gemma" with "Dbrx"
* remove # type: ignore
* don't hardcode vocab_size
* remove ToDo
* Re-add removed idefics2 line
* Update test to use tiny-random!
* Remove TODO
* Remove one more case of loading the entire dbrx-instruct in the tests
* Update src/transformers/models/dbrx/modeling_dbrx.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* address some comments
* small model
* add dbrx to tokenization_auto
* More docstrings with add_start_docstrings
* Dbrx for now
* add PipelineTesterMixin
* Update src/transformers/models/dbrx/configuration_dbrx.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* remove flash-attn2 import error
* fix docstring
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add useage example
* put on one line
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix ffn_act_fn
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* change "dbrx" to "DBRX" for display purposes.
* fix __init__.py?
* fix __init__.py
* fix README
* return the aux_loss
* remove extra spaces
* fix configuration_auto.py
* fix format in tokenization_auto
* remove new line
* add more useage examples
---------
Co-authored-by: Abhi Venigalla <abhi.venigalla@databricks.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Eitan Turok <eitan.turok@databricks.com>
Co-authored-by: Eitan Turok <150733043+eitanturok@users.noreply.github.com>
Co-authored-by: Wing Lian <wing.lian@gmail.com>
Co-authored-by: Eitan Turok <eitanturok@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Mihir Patel <mihir.v.patel7@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add jamba arch
* apply "make fix-copies" changes
* fix link to model in JambaConfig docstring
* Add n_ctx in modeling file because repo-consistency wants that
* Add jamba to flash attention and sdpa documentation
* mamba dt_proj quant fix now works for LoRA as well
* override test_left_padding_compatibility and use a more permissive tolerance. left padding numerical difference are accentuated by mamba layers
* add jamba to tokenization auto
* fix comments of shape (PR #24 in the model page: https://huggingface.co/ai21labs/Jamba-v0.1/discussions/24)
* simple PR fixes
* remove unnecessary kwargs from JambaAttentionDecoderLayer and JambaMambaDecoderLayer
* remove the LoRA hack for the mamba dt_proj bias. It was solved in huggingface/peft#1530 (https://github.com/huggingface/peft/pull/1530)
* Add copied comment on JambaMLP (it's the same as MixtralMLP)
* remove padding_mask warnings. It's not supported anymore
* fix docstring. Float instead of int
* A few more minor PR fixes
* (1) lowercase names for mamba layernorms (2) remove _apply_inner_layernorms and do it directly in the forward pass
* Return None attention weights from mamba layers. Append to all attentions only if not None.
* remove some leftover jamba archive lists
* Better separation between expert vs non-expert layers. non-expert layers return None as router_logits, and it is not concatenated to all_router_logits returned from JambaModel
* no need to take router_logits at config.expert_layer_offset anymore. result.router_logits now holds results only for expert layers
* Add Jamba paper on READMEs
* (1) rename n_ctx -> max_position_embeddings (2) don't use it in the modeling file since it's not needed (set it as an exception to check_config_attributes)
* Add copied from comment
* remove the code path for apply_inner_layernorms=False. Jamba always has the inner mamba layernorms
* clearer docstring for _convert_to_standard_cache
* style fixes
* Change calc_logits_for_entire_prompt (bool) to num_logits_to_keep (int). Adapt assisted decoding code tp use it. Also small change in low memory beam search decoding path to support this new int value in model_inputs
* rename test so it still overrides what its meant to override
* draft
* oups
* nit
* remove more complexe logic
* fix names used in config
* fix fix fix
* style
* fix some more failing tests
* generate did not init the cache 🙃
* more small nits
* typo
* config.mamba_expand * config.hidden_size for the intermediate size of the mamba shapes
* fix init of pkv with torch.tensor()
* empty tensor
* fix some init issues
* stupid changes required by generate because it does not even support it's own DynamicCache class
* more fixes
* fix general assisted gen cache_position bug
* tests passing
* Add offsets and periods as SPECIAL_CASES_TO_ALLOW in check_config_attributes.py
* fix reorder_cache to reorder mamba states and override some more functions in HybridMambaAttentionDynamicCache
* no need to override test_past_key_values_format() and _check_past_key_values_for_generate() in tests anymore
* fix docstrings and typehints for past_key_values
* style fixes
* fix docs
* change typehint due to copy from Mixtral
* forgot import
* import order
* Add configuration_jamba and modeling_jamba to not_doctested because the model is too big to download (in docstring of JambaForCausalLM.forward)
* Add integration test with tiny tandom Jamba model on hub
* fix flash attention cache shapes
* bring back forgotten hidden states
* rename HybridMambaAttentionDynamicCache.seqlen_offset to has_previous_state (and make bool) and bugfix - it should be set to True after a finished forward pass of the entire model
* align integration test after modeling fixes
* bugfix - mamba can use precomputed states only of forward pass is on a single token
* bugfix - mamba can use precomputed states only if they match the batch size
* typo
* remove making _prepare_4d_causal_attention_mask a leaf function
* stop using past_seq_len.get_seq_length(). Use cache positions instead. Adjust test (test_decoder_model_past_with_large_inputs) accordingly
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
* Add OLMo using add-new-model-like with Llama
* Fix incorrect tokenizer for OLMo
* Copy-paste relevant OLMo methods and their imports
* Add OLMo config
* Modify OLMo config to follow HF conventions
* Remove unneeded Llama code from OLMo model
* Add ability for OLMo model to output attentions
* Add OLMoPreTrainedModel and OLMoModel
* Add OLMoForCausalLM
* Minor fixes to OLMo model for style and missing functions
* Implement OLMo tokenizer
* Implement OLMo to HF conversion script
* Add tests for OLMo model
* Add tests for OLMo fast tokenizer
* Add auto-generated dummy objects
* Remove unimplemented OLMo classes from auto and init classes and re-format
* Add README and associated auto-generated files
* Use OLMo names for common properties
* Run make fixup
* Remove `|` from OLMo typing
* Remove unneeded tokenization_olmo.py
* Revert model, config and converter to add-new-model-like Llama
* Move logic for adding bos/eos token into GPTNeoxTokenizerFast
* Change OLMoConfig defaults to match OLMo-7B
* Use GPTNeoXToknizerFast in OLMo tokenizer tests
* Modify auto-generated OLMoModelTests to work for OLMo
* Add non-parametric layer norm OLMoLayerNorm
* Update weight conversion script for OLMo
* Fix __init__ and auto structure for OLMo
* Fix errors from make fixup
* Remove OLMoTokenizerFast from documentation
* Add missing 'Copied from' for OLMoModel._update_causal_mask
* Run make fix-copies
* Rearrange string replacements in OLMoForCausalLM Copied from
* Move OLMo and Llama CausalLM.forward example into global constants
* Fix OLMO_GENERATION_EXAMPLE doc string typo
* Add option for qkv clipping to OLMo
* Rearrange OLMoConfig kwargs in convert_olmo_weights_to_hf
* Add clip_qkv to OLMoConfig in convert_olmo_weights_to_hf
* Fix OLMo tokenization bug using conversion script
* Keep model in full precision after conversion
* Do not add eos token automatically
* Update references to OLMo model in HF Hub
* Do not add eos token during encoding by default
* Fix Llama generation example
* Run make fixup
* OLMo 7B integration test fix
* Remove unneeded special case for OLMoConfig
* OLMo 7B Twin 2T integration test fix
* Fix test_model_7b_greedy_generation
* Remove test_compile_static_cache
* Fix OLMo and Llama generation example
* Run make fixup
* Revert "OLMo 7B integration test fix"
This reverts commit 4df56a4b15.
* Revert "OLMo 7B Twin 2T integration test fix"
This reverts commit 9ff65a4a29.
* Ungate 7B integration tests and fix greedy generation test
* Add retries for flaky test_eager_matches_sdpa_generate
* Fix output of doc example for OLMoForCausalLM.forward
* Downsize OLMo doc test for OLMoForCausalLM.forward to 1B model
* Try fix incorrect characters in OLMoForCausalLM.forward doct test
* Try fix incorrect characters in OLMoForCausalLM.forward doc test using end quotes
* Remove pretraining_tp from OLMo config and model
* Add missing 'Copied from' instances
* Remove unneeded causal_mask from OLMoModel
* Revert Llama changes
* Ignore copy for OLMoForCausalLM.forward
* Change 'OLMo' to 'Olmo' in classes
* Move minimal OLMo tokenization tests to model tests
* Add missed 'Copied from' for repeat_kv
* Add create token type ids to CodeGenTokenizer
* Fix inconsistent length of token type ids
* Format source codes
* Fix inconsistent order of methods
* Update docstring
* add test_tokenizer_integration test
* Format source codes
* Add `copied from` comment to CodeGenTokenizerFast
* Add doc of create_token_type_ids_from_sequences
* Make return_token_type_ids False by default
* Make test_tokenizer_integration as slow test
* Add return_token_type_ids to tokenizer init arg
* Add test for tokenizer's init return_token_type_ids
* Format source codes
* Configuring Translation Pipelines documents update #27753
Configuring Translation Pipelines documents update
* Language Format Addition
* adding supported list of languages list
