mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-31 02:02:21 +06:00
a265600c60
* add sdpa to OPT
* chore: remove redundant whitespace in OPTDecoder class
* fixup
* bug fix
* add sdpa and attention generate test
* fixup
* Refactor OPTAttention forward method for improved readability and maintainability
* undo refactor for _shape and key,val states
* add OPT to doc, fixup didn't find it for some reason
* change order
* change default attn_implemntation in testing to eager
* [run-slow] opt
* change test_eager_matches_sdpa_generate to the one llama
* Update default attention implementation in testing common
* [run-slow] opt
* remove uneeded print
* [run-slow] opt
* refactor model testers to have attn_implementation="eager"
* [run-slow] opt
* convert test_eager_matches_sdpa_generate to opt-350M
* bug fix when creating mask for opt
* [run-slow] opt
* if layer head mask default to eager
* if head mask is not none fall to eager
* [run-slow] opt
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Clean up Unpack imports (#33631)
clean up Unpack imports
* Fix DPT /Dinov2 sdpa regression on main (#33660)
* fallback to eager if output attentions.
* fix copies
* handle dependency errors in check_imports (#33622)
* handle dependency errors in check_imports
* change log level to warning
* add back self.max_position_embeddings = config.max_position_embeddings (#33550)
* add back self.max_position_embeddings = config.max_position_embeddings
* fix-copies
* Fix Llava conversion for LlavaQwen2ForCausalLM with Clip vision tower (#33613)
fix llavaqwen2 model conversion
* Uniformize kwargs for Udop processor and update docs (#33628)
* Add optional kwargs and uniformize udop
* cleanup Unpack
* nit Udop
* Generation: deprecate `PreTrainedModel` inheriting from `GenerationMixin` (#33203)
* Enable BNB multi-backend support (#31098)
* 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
|
||
|---|---|---|
| .. | ||
| internal | ||
| main_classes | ||
| model_doc | ||
| quantization | ||
| tasks | ||
| _config.py | ||
| _redirects.yml | ||
| _toctree.yml | ||
| accelerate.md | ||
| add_new_model.md | ||
| add_new_pipeline.md | ||
| agents_advanced.md | ||
| agents.md | ||
| attention.md | ||
| autoclass_tutorial.md | ||
| benchmarks.md | ||
| bertology.md | ||
| big_models.md | ||
| chat_templating.md | ||
| community.md | ||
| contributing.md | ||
| conversations.md | ||
| create_a_model.md | ||
| custom_models.md | ||
| debugging.md | ||
| deepspeed.md | ||
| fast_tokenizers.md | ||
| fsdp.md | ||
| generation_strategies.md | ||
| gguf.md | ||
| glossary.md | ||
| how_to_hack_models.md | ||
| hpo_train.md | ||
| index.md | ||
| installation.md | ||
| kv_cache.md | ||
| llm_optims.md | ||
| llm_tutorial_optimization.md | ||
| llm_tutorial.md | ||
| model_memory_anatomy.md | ||
| model_sharing.md | ||
| model_summary.md | ||
| modular_transformers.md | ||
| multilingual.md | ||
| notebooks.md | ||
| pad_truncation.md | ||
| peft.md | ||
| perf_hardware.md | ||
| perf_infer_cpu.md | ||
| perf_infer_gpu_one.md | ||
| perf_torch_compile.md | ||
| perf_train_cpu_many.md | ||
| perf_train_cpu.md | ||
| perf_train_gpu_many.md | ||
| perf_train_gpu_one.md | ||
| perf_train_special.md | ||
| perf_train_tpu_tf.md | ||
| performance.md | ||
| perplexity.md | ||
| philosophy.md | ||
| pipeline_tutorial.md | ||
| pipeline_webserver.md | ||
| pr_checks.md | ||
| preprocessing.md | ||
| quicktour.md | ||
| run_scripts.md | ||
| sagemaker.md | ||
| serialization.md | ||
| task_summary.md | ||
| tasks_explained.md | ||
| testing.md | ||
| tf_xla.md | ||
| tflite.md | ||
| tiktoken.md | ||
| tokenizer_summary.md | ||
| torchscript.md | ||
| trainer.md | ||
| training.md | ||
| troubleshooting.md | ||