- 14 Feb, 2024 7 commits
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JB (Don) authored
* Add tie_weights() to LM heads and set bias in set_output_embeddings() The bias were not tied correctly in some LM heads, and this change should fix that. * Moving test_save_and_load_low_cpu_mem_usage to ModelTesterMixin * Adding _tie_weights() to MPNet and Vilt * Skip test for low cpu mem usage for Deta/DeformableDetr since they cannot init on meta device * Rename to test name to save_load to match the convention
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Raushan Turganbay authored
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Zach Mueller authored
* Introduce acceleratorconfig dataclass * Extra second warn * Move import * Try moving import under is_accelerate_available * Quality * Apply suggestions from code review Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Clean * Remove to_kwargs * Change version * Improve tests by including dispatch and split batches * Improve reliability * Update tests/trainer/test_trainer.py Co-authored-by:
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Huazhong Ji authored
Co-authored-by:unit_test <test@unit.com>
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Andrei Panferov authored
* aqlm init * calibration and dtypes * docs * Readme update * is_aqlm_available * Simpler link in docs * Test TODO real reference * init _import_structure fix * AqlmConfig autodoc * integration aqlm * integrations in tests * docstring fix * legacy typing * Less typings * More kernels information * Performance -> Accuracy * correct tests * remoced multi-gpu test * Update docs/source/en/quantization.md Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update src/transformers/utils/quantization_config.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Brought back multi-gpu tests * Update src/transformers/integrations/aqlm.py Co-authored-by:
Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update tests/quantization/aqlm_integration/test_aqlm.py Co-authored-by:
Andrei Panferov <blacksamorez@yandex-team.ru> Co-authored-by:
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NielsRogge authored
* First draft * Add CLIPForImageClassification * Remove scripts * Fix doctests
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Jonathan Tow authored
* Add `StableLM` * fix(model): re-create from `huggingface-cli add-new-model-like persimmon` * fix: re-add changes to address comments * fix(readme): add links to paper * fix(tokenization_auto): remove `GPTNeoXTokenizerFastFast` ref * fix(tests): re-add `@slow` decorator to integration tests * fix(tests): import slow... * fix(readme_hd): remove whitespace edit * fix(tokenizer): auto tokenizer tuple * skip doctests for `modeling_stablelm`
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- 13 Feb, 2024 4 commits
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amyeroberts authored
* Update the processing so bbox coords are adjusted for padding * Just pad masks * Tidy up, add tests * Better tests * Fix yolos and mark as slow for pycocotols * Fix yolos - return_tensors * Clarify padding and normalization behaviour
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Joao Gante authored
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Hiroshi Matsuda authored
* add sudachi_projection option * Upgrade sudachipy>=0.6.8 * add a test case for sudachi_projection * Compatible with older versions of SudachiPy * make fixup * make style * error message for unidic download * revert jumanpp test cases * format options for sudachi_projection Co-authored-by:
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Arthur authored
* refactor with addedtokens decoder * style * get rid of lang code to id * style * keep some things for BC * update tests * add the mask token at the end of the vocab * nits * nits * fix final tests * style * nits * Update src/transformers/models/nllb/tokenization_nllb_fast.py Co-authored-by:
avidale <dale.david@mail.ru> * Update Co-authored-by:
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- 12 Feb, 2024 3 commits
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Klaus Hipp authored
Add language identifiers to code blocks
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Joao Gante authored
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NielsRogge authored
* Fix pipeline * Remove print statements * Address comments * Address issue * Remove unused imports
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- 08 Feb, 2024 2 commits
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Raushan Turganbay authored
* support batched input for decoder start ids * Fix typos Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * minor changes * fix: decoder_start_id as list * empty commit * empty commit * empty commit * empty commit * empty commit * empty commit * empty commit * empty commit * empty commit --------- Co-authored-by:
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Arthur authored
Co-authored-by:
fxmarty <9808326+fxmarty@users.noreply.github.com> Co-authored-by:
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- 07 Feb, 2024 1 commit
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Daniel Korat authored
* change warning to exception * Update src/transformers/generation/utils.py Co-authored-by:
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- 06 Feb, 2024 4 commits
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Yih-Dar authored
* check * check * check --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar authored
* fix * fix --------- Co-authored-by: -
nakranivaibhav authored
* This is a test commit * testing commit * final commit with some changes * Removed copy statement * Fixed formatting issues * Fixed error added past_key_values in the forward method * Fixed a trailing whitespace. Damn the formatting rules are strict * Added the copy statement
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- 05 Feb, 2024 3 commits
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amyeroberts authored
* Draft pipeline * Fixup * Fix docstrings * Update doctest * Update pipeline_model_mapping * Update docstring * Update tests * Update src/transformers/pipelines/image_feature_extraction.py Co-authored-by:
Omar Sanseviero <osanseviero@gmail.com> * Fix docstrings - review comments * Remove pipeline mapping for composite vision models * Add to pipeline tests * Remove for flava (multimodal) * safe pil import * Add requirements for pipeline run * Account for super slow efficientnet * Review comments * Fix tests * Swap order of kwargs * Use build_pipeline_init_args * Add back FE pipeline for Vilt * Include image_processor_kwargs in docstring * Mark test as flaky * Update TODO * Update tests/pipelines/test_pipelines_image_feature_extraction.py Co-authored-by:
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Yoach Lacombe authored
* Correct wav2vec2-bert inputs_to_logits_ratio * correct ratio * correct ratio, clean asr pipeline * refactor on one line
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Nicolas Patry authored
* [WIP] Hard error when ignoring tensors. * Better selection/error when saving a checkpoint. - Find all names we should normally drop (those are in the transformers config) - Find all disjoint tensors (for those we can safely trigger a copy to get rid of the sharing before saving) - Clone those disjoint tensors getting rid of the issue - Find all identical names (those should be declared in the config but we try to find them all anyway.) - For all identical names: - If they are in the config, just ignore them everything is fine - If they are not, warn about them. - For all remainder tensors which are shared yet neither identical NOR disjoint. raise a hard error. * Adding a failing test on `main` that passes here. * We don't need to keep the subfolder logic in this test. * Apply suggestions from code review Co-authored-by:
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- 02 Feb, 2024 4 commits
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amyeroberts authored
Mark test as flaky
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Yih-Dar authored
* fix / skip some tests before we can switch to torch 2.2 * style --------- Co-authored-by: -
Juri Ganitkevitch authored
* Add missing None check for hf_quantizer * Add test, fix logic. * make style * Switch test model to Mistral * Comment * Update tests/test_modeling_utils.py --------- Co-authored-by: -
Klaus Hipp authored
* Fix typos and grammar mistakes in docs and examples * Fix typos in docstrings and comments * Fix spelling of `tokenizer` in model tests * Remove erroneous spaces in decorators * Remove extra spaces in Markdown link texts
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- 01 Feb, 2024 2 commits
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fxmarty authored
* fix symbolic_trace with kv cache * comment & better test
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JB (Don) authored
* Adding [T5/MT5/UMT5]ForTokenClassification * Add auto mappings for T5ForTokenClassification and variants * Adding ForTokenClassification to the list of models * Adding attention_mask param to the T5ForTokenClassification test * Remove outdated comment in test * Adding EncoderOnly and Token Classification tests for MT5 and UMT5 * Fix typo in umt5 string * Add tests for all the existing MT5 models * Fix wrong comment in dependency_versions_table * Reverting change to common test for _keys_to_ignore_on_load_missing The test is correctly picking up redundant keys in _keys_to_ignore_on_load_missing. * Removing _keys_to_ignore_on_missing from MT5 since the key is not used in the model * Add fix-copies to MT5ModelTest
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- 31 Jan, 2024 4 commits
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Joao Gante authored
DeepSpeed: hardcode `torch.arange` dtype on `float` usage to avoid incorrect initialization (#28760)
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Kian Sierra McGettigan authored
* direct copy from llama work * mistral modules forward pass working * flax mistral forward pass with sliding window * added tests * added layer collection approach * Revert "added layer collection approach" This reverts commit 0e2905bf2236ec323163fc1a9f0c016b21aa8b8f. * Revert "Revert "added layer collection approach"" This reverts commit fb17b6187ac5d16da7c461e1130514dc3d137a43. * fixed attention outputs * added mistral to init and auto * fixed import name * fixed layernorm weight dtype * freeze initialized weights * make sure conversion consideres bfloat16 * added backend * added docstrings * added cache * fixed sliding window causal mask * passes cache tests * passed all tests * applied make style * removed commented out code * applied fix-copies ignored other model changes * applied make fix-copies * removed unused functions * passed generation integration test * slow tests pass * fixed slow tests * changed default dtype from jax.numpy.float32 to float32 for docstring check * skip cache test for FlaxMistralForSequenceClassification since if pad_token_id in input_ids it doesn't score previous input_ids * updated checkpoint since from_pt not included * applied black style * removed unused args * Applied styling and fixup * changed checkpoint for doc back * fixed rf after adding it to hf hub * Add dummy ckpt * applied styling * added tokenizer to new ckpt * fixed slice format * fix init and slice * changed ref for placeholder TODO * added copies from Llama * applied styling * applied fix-copies * fixed docs * update weight dtype reconversion for sharded weights * removed Nullable input ids * Removed unnecessary output attentions in Module * added embedding weight initialziation * removed unused past_key_values * fixed deterministic * Fixed RMS Norm and added copied from * removed input_embeds * applied make style * removed nullable input ids from sequence classification model * added copied from GPTJ * added copied from Llama on FlaxMistralDecoderLayer * added copied from to FlaxMistralPreTrainedModel methods * fix test deprecation warning * freeze gpt neox random_params and fix copies * applied make style * fixed doc issue * skipped docstring test to allign # copied from * applied make style * removed FlaxMistralForSequenceClassification * removed unused padding_idx * removed more sequence classification * removed sequence classification * applied styling and consistency * added copied from in tests * removed sequence classification test logic * applied styling * applied make style * removed freeze and fixed copies * undo test change * changed repeat_kv to tile * fixed to key value groups * updated copyright year * split casual_mask * empty to rerun failed pt_flax_equivalence test FlaxWav2Vec2ModelTest * went back to 2023 for tests_pr_documentation_tests * went back to 2024 * changed tile to repeat * applied make style * empty for retry on Wav2Vec2
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Patrick von Platen authored
* up * Fix more * Correct more * Fix more tests * fix fast tests * Fix more * fix more * push all files * finish all * make style * Fix timestamp wrap * make style * make style * up * up * up * Fix lang detection behavior * Fix lang detection behavior * Add lang detection test * Fix lang detection behavior * make style * Update src/transformers/models/whisper/generation_whisper.py Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * better error message * make style tests * add warning --------- Co-authored-by:
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tom-p-reichel authored
* test that tied output embeddings aren't initialized on load * don't initialize the output embeddings if we're going to tie them to the input embeddings
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- 30 Jan, 2024 4 commits
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Matt authored
* Port core files + ESM (because ESM code is odd) * Search-replace in modelling code * Fix up transfo_xl as well * Fix other core files + tests (still need to add correct import to tests) * Fix cookiecutter * make fixup, fix imports in some more core files * Auto-add imports to tests * Cleanup, add imports to sagemaker tests * Use correct exception for importing tf_keras * Fixes in modeling_tf_utils * make fixup * Correct version parsing code * Ensure the pipeline tests correctly revert to float32 after each test * Ensure the pipeline tests correctly revert to float32 after each test * More tf.keras -> keras * Add dtype cast * Better imports of tf_keras * Add a cast for tf.assign, just in case * Fix callback imports
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amyeroberts authored
* Enable instantiating model with pretrained backbone weights * Remove doc updates until changes made in modeling code * Use load_backbone instead * Add use_timm_backbone to the model configs * Add missing imports and arguments * Update docstrings * Make sure test is properly configured * Include recent DPT updates
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Poedator authored
* squashed earlier commits for easier rebase * rm rebase leftovers * 4bit save enabled @quantizers * TMP gptq test use exllama * fix AwqConfigTest::test_wrong_backend for A100 * quantizers AWQ fixes * _load_pretrained_model low_cpu_mem_usage branch * quantizers style * remove require_low_cpu_mem_usage attr * rm dtype arg from process_model_before_weight_loading * rm config_origin from Q-config * rm inspect from q_config * fixed docstrings in QuantizationConfigParser * logger.warning fix * mv is_loaded_in_4(8)bit to BnbHFQuantizer * is_accelerate_available error msg fix in quantizer * split is_model_trainable in bnb quantizer class * rm llm_int8_skip_modules as separate var in Q * Q rm todo * fwd ref to HFQuantizer in type hint * rm note re optimum.gptq.GPTQQuantizer * quantization_config in __init__ simplified * replaced NonImplemented with create_quantized_param * rm load_in_4/8_bit deprecation warning * QuantizationConfigParser refactoring * awq-related minor changes * awq-related changes * awq config.modules_to_not_convert * raise error if no q-method in q-config in args * minor cleanup * awq quantizer docstring * combine common parts in bnb process_model_before_weight_loading * revert test_gptq * .process_model_ cleanup * restore dict config warning * removed typevars in quantizers.py * cleanup post-rebase 16 jan * QuantizationConfigParser classmethod refactor * rework of handling of unexpected aux elements of bnb weights * moved q-related stuff from save_pretrained to quantizers * refactor v1 * more changes * fix some tests * remove it from main init * ooops * Apply suggestions from code review Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by:
younesbelkada <younesbelkada@gmail.com> Co-authored-by:
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Omar Sanseviero authored
* Update quantization_config.py * Style * Protect from setting directly * add tests * Update tests/quantization/bnb/test_4bit.py Co-authored-by:
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- 29 Jan, 2024 2 commits
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amyeroberts authored
* Make test_constrained_beam_search_generate as flaky * Update tests/generation/test_utils.py
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Wesley Gifford authored
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🐛 fix .max bug * remove prediction_length from regression output dimensions * fix parameter names, fix output names, update tests * ensure shape for PatchTST * ensure output shape for PatchTSMixer * update model, batch, and expected for regression distribution test * update test expected Signed-off-by:Wesley M. Gifford <wmgifford@us.ibm.com> * Update tests/models/patchtst/test_modeling_patchtst.py Co-authored-by:
Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by:
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