* remove to restiction for 4-bit model
* Update src/transformers/modeling_utils.py
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* bitsandbytes: prevent dtype casting while allowing device movement with .to or .cuda
* quality fix
* Improve warning message for .to() and .cuda() on bnb quantized models
---------
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* don't run custom when not needed?
* update test fetcher filtering
* fixup and updates
* update
* update
* reduce burden
* nit
* nit
* mising comma
* this?
* this?
* more parallelism
* more
* nit for real parallelism on tf and torch examples
* update
* update
* update
* update
* update
* update
* update
* update
* update
* update
* update
* update
* update to make it more custom
* update to make it more custom
* update to make it more custom
* update to make it more custom
* update
* update
* update
* update
* update
* update
* use correct path
* fix path to test files and examples
* filter-tests
* filter?
* filter?
* filter?
* nits
* fix naming of the artifacts to be pushed
* list vs files
* list vs files
* fixup
* fix list of all tests
* fix the install steps
* fix the install steps
* fix the config
* fix the config
* only split if needed
* only split if needed
* extend should fix it
* extend should fix it
* arg
* arg
* update
* update
* run tests
* run tests
* run tests
* more nits
* update
* update
* update
* update
* update
* update
* update
* simpler way to show the test, reduces the complexity of the generated config
* simpler way to show the test, reduces the complexity of the generated config
* style
* oups
* oups
* fix import errors
* skip some tests for now
* update doctestjob
* more parallelism
* fixup
* test only the test in examples
* test only the test in examples
* nits
* from Arthur
* fix generated congi
* update
* update
* show tests
* oups
* oups
* fix torch job for now
* use single upload setp
* oups
* fu**k
* fix
* nit
* update
* nit
* fix
* fixes
* [test-all]
* add generate marker and generate job
* oups
* torch job runs not generate tests
* let repo utils test all utils
* UPdate
* styling
* fix repo utils test
* more parallel please
* don't test
* update
* bit more verbose sir
* more
* hub were skipped
* split by classname
* revert
* maybe?
* Amazing catch
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* fix
* update
* update
* maybe non capturing
* manual convert?
* pass artifacts as parameters as otherwise the config is too long
* artifact.json
* store output
* might not be safe?
* my token
* mmm?
* use CI job IS
* can't get a proper id?
* ups
* build num
* update
* echo url
* this?
* this!
* fix
* wget
* ish
* dang
* udpdate
* there we go
* update
* update
* pass all
* not .txt
* update
* fetcg
* fix naming
* fix
* up
* update
* update
* ??
* update
* more updates
* update
* more
* skip
* oups
* pr documentation tests are currently created differently
* update
* hmmmm
* oups
* curl -L
* update
* ????
* nit
* mmmm
* ish
* ouf
* update
* ish
* update
* update
* updatea
* nit
* nit
* up
* oups
* documentation_test fix
* test hub tests everything, just marker
* update
* fix
* test_hub is the only annoying one now
* tf threads?
* oups
* not sure what is happening?
* fix?
* just use folder for stating hub
* I am getting fucking annoyed
* fix the test?
* update
* uupdate
* ?
* fixes
* add comment!
* nit
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* first attempt at allowing both conversions from codestral and from the original mamba ssm
* allow fp16, seems default for mamba2
* dtype fix
* simplify codestral check, dont overwrite pad/eos/bos when codestral
* change file -> directory
* use path join to be safe
* style
* apply code review
- add util mamba2 tokenizer (gptneox with left padding)
- add models dict
* fix copies
* add tokenizer to docs
* empty commit to check for weird err
* make conversion user dependent on model type, defaults for original paper models
* small comment nit
* remove norm_before_gate in conversion
* simplify model dict by using shared keys directly + remove unnecessary attributes
* fix tokenization: remove separate mamba2 tokenizer, add padding option as kwarg to gptneox one and reuse it for the conversion script
* simplify even further as we pass padding side via **kwargs already
* pass module to Params4bit.from_prequantized to ensure quant_state
* make sure to check bnb version
* revert min bnb version and use inspect on method instead
* use version instead of inspect to prevent performance hit
* make the property name readable
* Customising the separator used for splicing in DataCollatorWithFlattening
* update DataCollatorWithFlattening docs
---------
Co-authored-by: weifangyuan <i.weifangyuan@yuewen.com>
* 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
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Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* init fix
* fix mask during cached forward, move mask related stuff to own function
* adjust tests as left padding does not change logits as much anymore + batch gen (with todo on logits comp)
* revert overwriting new integration tests
* move some comments to docstring
* 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.
* fix redundant checkpointing in example scripts
* Update examples/pytorch/image-classification/run_image_classification_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/translation/run_translation_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/token-classification/run_ner_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/text-classification/run_glue_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/summarization/run_summarization_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/language-modeling/run_mlm_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/language-modeling/run_fim_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/language-modeling/run_clm_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/image-pretraining/run_mim_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/instance-segmentation/run_instance_segmentation_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/multiple-choice/run_swag_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/question-answering/run_qa_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/object-detection/run_object_detection_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Add a fix for the case when tokenizers are passed as a string
* Support image processors and feature extractors as well
* Reverting load_feature_extractor and load_image_processor
* Add test
* Test is torch-only
* Add tests for preprocessors and feature extractors and move test
* Extremely experimental fix
* Revert that change, wrong branch!
* Typo!
* Split tests
* update ExportableState callbacks state before saving trainer_state on save_checkpoint
* run make fixup and fix format
* manage multiple stateful callbacks of same class
