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- 18 Oct, 2022 3 commits
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NielsRogge authored
* Improve DETR models * Fix Deformable DETR loss and matcher * Fixup * Fix integration tests * Improve variable names * Apply suggestion * Fix copies * Fix DeformableDetrLoss * Make Conditional DETR copy from Deformable DETR * Copy from deformable detr's hungarian matcher * Fix bug
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Arthur authored
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Arthur authored
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- 17 Oct, 2022 6 commits
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amyeroberts authored
* Adapt FE methods to transforms library * Mixin for saving the image processor * Base processor skeleton * BatchFeature for packaging image processor outputs * Initial image processor for GLPN * REmove accidental import * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Add rescale back and remove ImageType * fix import mistake * Fix enum var reference * Can transform and specify image data format * Remove redundant function * Update reference * Data format flag for rescale * Fix typo * Fix dimension check * Fixes to make IP and FE outputs match * Add tests for transforms * Add test for utils * Update some docstrings * Make sure in channels last before converting to PIL * Remove default to numpy batching * Fix up * Add docstring and model_input_types * Use feature processor config from hub * Alias GLPN feature extractor to image processor * Alias feature extractor mixin * Add return_numpy=False flag for resize * Fix up * Fix up * Use different frameworks safely * Safely import PIL * Call function checking if PIL available * Only import if vision available * Address Sylvain PR comments Co-authored-by: Sylvain.gugger@gmail.com * Apply suggestions from code review Co-authored-by:
Sylvain Gugger <Sylvain.gugger@gmail.com> Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/image_transforms.py Co-authored-by:
Alara Dirik <8944735+alaradirik@users.noreply.github.com> * Update src/transformers/models/glpn/feature_extraction_glpn.py Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Add in docstrings * Fix TFSwinSelfAttention to have relative position index as non-trainable weight (#18226) Signed-off-by:
Seunghwan Hong <seunghwan@scatterlab.co.kr> * Refactor `TFSwinLayer` to increase serving compatibility (#18352) * Refactor `TFSwinLayer` to increase serving compatibility Signed-off-by:
Seunghwan Hong <harrydrippin@gmail.com> Co-Authored-By:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com> * Remove py.typed (#18485) * Fix pipeline tests (#18487) * Fix pipeline tests * Make sure all pipelines tests run with init changes * Use new huggingface_hub tools for download models (#18438) * Draft new cached_file * Initial draft for config and model * Small fixes * Fix first batch of tests * Look in cache when internet is down * Fix last tests * Bad black, not fixing all quality errors * Make diff less * Implement change for TF and Flax models * Add tokenizer and feature extractor * For compatibility with main * Add utils to move the cache and auto-do it at first use. * Quality * Deal with empty commit shas * Deal with empty etag * Address review comments * Fix `test_dbmdz_english` by updating expected values (#18482) Co-authored-by:
😬 (#18489) * Delete valohai.yaml * NLP => ML * typo * website supports https * datasets * 60k + modalities * unrelated link fixing for accelerate * Ok those links were actually broken * Fix link * Make `AutoTokenizer` auto-link * wording tweak * add at least one non-nlp task * `transformers-cli login` => `huggingface-cli login` (#18490) * zero chance anyone's using that constant no? * `transformers-cli login` => `huggingface-cli login` * `transformers-cli repo create` => `huggingface-cli repo create` * `make style` * Add seed setting to image classification example (#18519) * [DX fix] Fixing QA pipeline streaming a dataset. (#18516) * [DX fix] Fixing QA pipeline streaming a dataset. QuestionAnsweringArgumentHandler would iterate over the whole dataset effectively killing all properties of the pipeline. This restores nice properties when using `Dataset` or `Generator` since those are meant to be consumed lazily. * Handling TF better. * Clean up hub (#18497) * Clean up utils.hub * Remove imports * More fixes * Last fix * update fsdp docs (#18521) * updating fsdp documentation * typo fix * Fix compatibility with 1.12 (#17925) * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * fix torch.onnx.symbolic_opset12 import * Reject bad version Co-authored-by:Ankur Goyal <ankur@impira.com> * New cache fixes: add safeguard before looking in folders (#18522) * unpin resampy (#18527) Co-authored-by:
✨ update to use interlibrary links instead of Markdown (#18500) * Add example of multimodal usage to pipeline tutorial (#18498) *📝 add example of multimodal usage to pipeline tutorial *🖍 apply feedbacks *🖍 apply niels feedback * [VideoMAE] Add model to doc tests (#18523) * Add videomae to doc tests * Add pip install decord Co-authored-by:Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local> * Update perf_train_gpu_one.mdx (#18532) * Update no_trainer.py scripts to include accelerate gradient accumulation wrapper (#18473) * Added accelerate gradient accumulation wrapper to run_image_classification_no_trainer.py example script * make fixup changes * PR comments * changed input to Acceletor based on PR comment, ran make fixup * Added comment explaining the sync_gradients statement * Fixed lr scheduler max steps * Changed run_clm_no_trainer.py script to use accelerate gradient accum wrapper * Fixed all scripts except wav2vec2 pretraining to use accelerate gradient accum wrapper * Added accelerate gradient accum wrapper for wav2vec2_pretraining_no_trainer.py script * make fixup and lr_scheduler step inserted back into run_qa_beam_search_no_trainer.py * removed changes to run_wav2vec2_pretraining_no_trainer.py script and fixed using wrong constant in qa_beam_search_no_trainer.py script * Add Spanish translation of converting_tensorflow_models.mdx (#18512) * Add file in spanish docs to be translated * Finish translation to Spanish * Improve Spanish wording * Add suggested changes from review * Spanish translation of summarization.mdx (#15947) (#18477) * Add Spanish translation of summarization.mdx * Apply suggestions from code review Co-authored-by:
Omar U. Espejel <espejelomar@gmail.com> Co-authored-by:
Thomas Wang <24695242+thomasw21@users.noreply.github.com> * more comments - added more comments on why we cast only floating point parameters * Update src/transformers/modeling_utils.py Co-authored-by:
📝 update metric with evaluate (#18535) * Restore _init_weights value in no_init_weights (#18504) * Recover _init_weights value in no_init_weights For potential nested use. In addition, users might modify private no_init_weights as well. * Apply suggestions from code review Co-authored-by:📝 update documentation build section (#18548) * `bitsandbytes` - `Linear8bitLt` integration into `transformers` models (#17901) * first commit * correct replace function * add final changes - works like charm! - cannot implement tests yet - tested * clean up a bit * add bitsandbytes dependencies * working version - added import function - added bitsandbytes utils file * small fix * small fix - fix import issue * fix import issues * Apply suggestions from code review Co-authored-by:Michael Benayoun <mickbenayoun@gmail.com> * add few comments * add more doctring + make style * more docstring * raise error when loaded in 8bit * make style * add warning if loaded on CPU * add small sanity check * fix small comment * add bitsandbytes on dockerfile * Improve documentation - improve documentation from comments * add few comments * slow tests pass on the VM but not on the CI VM * Fix merge conflict * make style * another test should pass on a multi gpu setup * fix bad import in testing file * Fix slow tests - remove dummy batches - no more CUDA illegal memory errors * odify dockerfile * Update docs/source/en/main_classes/model.mdx * Update Dockerfile * Update model.mdx * Update Dockerfile * Apply suggestions from code review * few modifications - lm head can stay on disk/cpu - change model name so that test pass * change test value - change test value to the correct output - torch bmm changed to baddmm in bloom modeling when merging * modify installation guidelines * Apply suggestions from code review Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * Update examples/tensorflow/test_tensorflow_examples.py Co-authored-by:
Julien Chaumond <julien@huggingface.co> * Address Julien's comments Co-authored-by:
📝 update philosophy to include other preprocessing classes *🖍 apply feedbacks * Properly move cache when it is not in default path (#18563) * Adds CLIP to models exportable with ONNX (#18515) * onnx config for clip * default opset as 14 * changes from the original repo * input values order fix * outputs fix * remove unused import * ran make fix-copies * black format * review comments: forward ref, import fix, model change revert, .to cleanup * make style * formatting fixes * revert groupvit * comment for cast to int32 * comment fix * make .T as .t() for onnx conversion * ran make fix-copies * remove unneeded comment Co-authored-by:Maxime Gardoni <maxime.gardoni@ecorobotix.com> * Fix resizing bug in OWL-ViT (#18573) * Fixes resizing bug in OWL-ViT * Defaults to square resize if size is set to an int * Sets do_center_crop default value to False * Fix LayoutLMv3 documentation (#17932) * fix typos * fix sequence_length docs of LayoutLMv3Model * delete trailing white spaces * fix layoutlmv3 docs more * apply make fixup & quality * change to two versions of input docstring * apply make fixup & quality * Skip broken tests * Change BartLearnedPositionalEmbedding's forward method signature to support Opacus training (#18486) * changing BartLearnedPositionalEmbedding forward signature and references to it * removing debugging dead code (thanks style checker) * blackened modeling_bart file * removing copy inconsistencies via make fix-copies * changing references to copied signatures in Bart variants * make fix-copies once more * using expand over repeat (thanks @michaelbenayoun) * expand instead of repeat for all model copies Co-authored-by:
Daniel Jones <jonesdaniel@microsoft.com> * german docs translation (#18544) * Create _config.py * Create _toctree.yml * Create index.mdx not sure about "du / ihr" oder "sie" * Create quicktour.mdx * Update _toctree.yml * Update build_documentation.yml * Update build_pr_documentation.yml * fix build * Update index.mdx * Update quicktour.mdx * Create installation.mdx * Update _toctree.yml * Deberta V2: Fix critical trace warnings to allow ONNX export (#18272) * Fix critical trace warnings to allow ONNX export * Force input to `sqrt` to be float type * Cleanup code * Remove unused import statement * Update model sew * Small refactor Co-authored-by:
dependabot[bot] <support@github.com> Signed-off-by:
dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * Bump nbconvert in /examples/research_projects/visual_bert (#18566) Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 6.0.1 to 6.3.0. - [Release notes](https://github.com/jupyter/nbconvert/releases) - [Commits](https://github.com/jupyter/nbconvert/compare/6.0.1...6.3.0 ) --- updated-dependencies: - dependency-name: nbconvert dependency-type: direct:production ... Signed-off-by:
Wang, Yi A <yi.a.wang@intel.com> * Update docs/source/en/perf_train_cpu_many.mdx Co-authored-by:
sanchit-gandhi <sanchit@huggingface.co> * mac m1 `mps` integration (#18598) * mac m1 `mps` integration * Update docs/source/en/main_classes/trainer.mdx Co-authored-by:
Dan Saattrup Nielsen <47701536+saattrupdan@users.noreply.github.com> * resolve comment Co-authored-by:
Stas Bekman <stas00@users.noreply.github.com> * Apply suggestions from code review * Apply suggestions from code review * Apply suggestions from code review * put in one block - put bash instructions in one block * update readme - refactor a bit hardware requirements * change text a bit * Apply suggestions from code review Co-authored-by:
Yih-Dar <2521628+ydshieh@users.noreply.github.com> * apply suggestions Co-authored-by:
lewtun <lewis.c.tunstall@gmail.com> Co-authored-by:
Amy Roberts <amyeroberts@users.noreply.github.com> Co-authored-by:
regisss <15324346+regisss@users.noreply.github.com> Co-authored-by:
Nicolas Patry <patry.nicolas@protonmail.com> Co-authored-by:
Sourab Mangrulkar <13534540+pacman100@users.noreply.github.com> Co-authored-by:
Ankur Goyal <ankrgyl@gmail.com> Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by:
Mishig Davaadorj <dmishig@gmail.com> Co-authored-by:
Rasmus Arpe Fogh Jensen <Rasmus.arpe@gmail.com> Co-authored-by:
Ian Castillo <7807897+donelianc@users.noreply.github.com> Co-authored-by:
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Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
Niklas Hansson <niklas.sven.hansson@gmail.com> Co-authored-by:
Thomas Chaigneau <t.chaigneau.tc@gmail.com> Co-authored-by:
YouJiacheng <1503679330@qq.com> Co-authored-by:
Matt <Rocketknight1@users.noreply.github.com> Co-authored-by:
Dhruv Karan <k4r4n.dhruv@gmail.com> Co-authored-by:
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Wonseok Lee (Jack) <rollerkid02@snu.ac.kr> Co-authored-by:
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Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by:
Niklas Muennighoff <n.muennighoff@gmail.com> Co-authored-by:
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Stefan Schweter <stefan@schweter.it> Co-authored-by:
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Sylvain Gugger authored
This reverts commit 35bd089a.
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Ayrton San Joaquin authored
* add return_tensors parameter for feature_extraction w/ test add return_tensor parameter for feature extraction Revert "Merge branch 'feature-extraction-return-tensor' of https://github.com/ajsanjoaquin/transformers into feature-extraction-return-tensor" This reverts commit d559da743b87914e111a84a98ba6dbb70d08ad88, reversing changes made to bbef89278650c04c090beb65637a8e9572dba222. * call parameter directly Co-authored-by:
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Ankur Goyal authored
* Fixes * update expected values * style * fix Co-authored-by: -
Matt authored
* Partial TF port for ESM model * Add ESM-TF tests * Add the various imports for TF-ESM * TF weight conversion almost ready * Stop ignoring the decoder weights in PT * Add tests and lots of fixes * fix-copies * Fix imports, add model docs * Add get_vocab() to tokenizer * Fix vocab links for pretrained files * Allow multiple inputs with a sep * Use EOS as SEP token because ESM vocab lacks SEP * Correctly return special tokens mask from ESM tokenizer * make fixup * Stop testing unsupported embedding resizing * Handle TF bias correctly * Skip all models with slow tokenizers in the token classification test * Fixing the batch/unbatcher of pipelines to accomodate the `None` being passed around. * Fixing pipeline bug caused by slow tokenizer being different. * Update src/transformers/models/esm/modeling_tf_esm.py Co-authored-by:
Your Name <you@example.com> Co-authored-by:
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Sivaudha authored
* Remove key word argument X from pipeline predict and transform methods As __call__ of pipeline clasees require one positional argument, passing the input as a keyword argument inside predict, transform methods, causing __call__ to fail. Hence in this commit the keyword argument is modified into positional argument. * Implement basic tests for scikitcompat pipeline interface * Seperate tests instead of running with parameterized based on framework as both frameworks will not be active at the same time
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- 14 Oct, 2022 8 commits
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Sylvain Gugger authored
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Arthur authored
* simplify loop * fix layer map split * update * update for special variables * add rag test * fixup * revert change : for next PR
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Nicolas Patry authored
* Improve error messaging for ASR pipeline. - Raise error early (in `_sanitize`) so users don't waste time trying to run queries with invalid params. - Fix the error was after using `config.inputs_to_logits_ratio` so our check was masked by the failing property does not exist. - Added some manual check on s2t for the error message. No non ctc model seems to be used by the default runner (they are all skipped). * Removing pdb. * Stop the early error it doesn't really work :(.
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Yih-Dar authored
Co-authored-by: -
Pi Esposito authored
* add suport for non fast tf bert tokenizer * add tests for non fast tf bert tokenizer * fix fast bert tf tokenizer flag * double tokenizers list on tf tokenizers test to aovid breaking zip on test output equivalence * reformat code with black to comply with code quality checks * trigger ci
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Yih-Dar authored
Co-authored-by: -
Sanchit Gandhi authored
* [Whisper] Don't return attention mask in feat extractor * remove attention mask from test * fix failing tests * quality
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amyeroberts authored
* Cast masks to np.unit8 before converting to PIL.Image.Image * Update tests * Fixup
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- 13 Oct, 2022 1 commit
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Sanchit Gandhi authored
* [Whisper] Freeze params of encoder * add tests
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- 12 Oct, 2022 6 commits
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Yih-Dar authored
* return None to avoid recursive call * Give error * Give error * Add test * More tests * Quality Co-authored-by: -
Sylvain Gugger authored
* Add a decorator for flaky tests * Quality * Don't break the rest * Address review comments * Fix test name * Fix typo and print to stderr
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amyeroberts authored
* Adapt FE methods to transforms library * Mixin for saving the image processor * Base processor skeleton * BatchFeature for packaging image processor outputs * Initial image processor for GLPN * REmove accidental import * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Add rescale back and remove ImageType * fix import mistake * Fix enum var reference * Can transform and specify image data format * Remove redundant function * Update reference * Data format flag for rescale * Fix typo * Fix dimension check * Fixes to make IP and FE outputs match * Add tests for transforms * Add test for utils * Update some docstrings * Make sure in channels last before converting to PIL * Remove default to numpy batching * Fix up * Add docstring and model_input_types * Use feature processor config from hub * Alias GLPN feature extractor to image processor * Alias feature extractor mixin * Add return_numpy=False flag for resize * Fix up * Fix up * Use different frameworks safely * Safely import PIL * Call function checking if PIL available * Only import if vision available * Address Sylvain PR comments Co-authored-by: Sylvain.gugger@gmail.com * Apply suggestions from code review Co-authored-by:
😬 (#18489) * Delete valohai.yaml * NLP => ML * typo * website supports https * datasets * 60k + modalities * unrelated link fixing for accelerate * Ok those links were actually broken * Fix link * Make `AutoTokenizer` auto-link * wording tweak * add at least one non-nlp task * `transformers-cli login` => `huggingface-cli login` (#18490) * zero chance anyone's using that constant no? * `transformers-cli login` => `huggingface-cli login` * `transformers-cli repo create` => `huggingface-cli repo create` * `make style` * Add seed setting to image classification example (#18519) * [DX fix] Fixing QA pipeline streaming a dataset. (#18516) * [DX fix] Fixing QA pipeline streaming a dataset. QuestionAnsweringArgumentHandler would iterate over the whole dataset effectively killing all properties of the pipeline. This restores nice properties when using `Dataset` or `Generator` since those are meant to be consumed lazily. * Handling TF better. * Clean up hub (#18497) * Clean up utils.hub * Remove imports * More fixes * Last fix * update fsdp docs (#18521) * updating fsdp documentation * typo fix * Fix compatibility with 1.12 (#17925) * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * fix torch.onnx.symbolic_opset12 import * Reject bad version Co-authored-by:✨ update to use interlibrary links instead of Markdown (#18500) * Add example of multimodal usage to pipeline tutorial (#18498) *📝 add example of multimodal usage to pipeline tutorial *🖍 apply feedbacks *🖍 apply niels feedback * [VideoMAE] Add model to doc tests (#18523) * Add videomae to doc tests * Add pip install decord Co-authored-by:📝 update metric with evaluate (#18535) * Restore _init_weights value in no_init_weights (#18504) * Recover _init_weights value in no_init_weights For potential nested use. In addition, users might modify private no_init_weights as well. * Apply suggestions from code review Co-authored-by:📝 update documentation build section (#18548) * `bitsandbytes` - `Linear8bitLt` integration into `transformers` models (#17901) * first commit * correct replace function * add final changes - works like charm! - cannot implement tests yet - tested * clean up a bit * add bitsandbytes dependencies * working version - added import function - added bitsandbytes utils file * small fix * small fix - fix import issue * fix import issues * Apply suggestions from code review Co-authored-by:📝 update philosophy to include other preprocessing classes *🖍 apply feedbacks * Properly move cache when it is not in default path (#18563) * Adds CLIP to models exportable with ONNX (#18515) * onnx config for clip * default opset as 14 * changes from the original repo * input values order fix * outputs fix * remove unused import * ran make fix-copies * black format * review comments: forward ref, import fix, model change revert, .to cleanup * make style * formatting fixes * revert groupvit * comment for cast to int32 * comment fix * make .T as .t() for onnx conversion * ran make fix-copies * remove unneeded comment Co-authored-by: -
NielsRogge authored
* Fix XCLIP doc tests * Add model to doc test list * Fix tests
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Ritik Nandwal authored
* Add initial files for depth estimation pipelines * Add test file for depth estimation pipeline * Update model mapping names * Add updates for depth estimation output * Add generic test * Hopefully fixing the tests. * Check if test passes * Add make fixup and make fix-copies changes after rebase with main * Rebase with main * Fixing up depth pipeline. * This is not used anymore. * Fixing the test. `Image` is a module `Image.Image` is the type. * Update docs/source/en/main_classes/pipelines.mdx Co-authored-by:
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NielsRogge authored
* First draft * Fix more things * Improve more things * Remove some head models * Fix more things * Add missing layers * Remove tokenizer * Fix more things * Fix copied from statements * Make all tests pass * Remove print statements * Remove files * Fix README and docs * Add integration test and fix organization * Add tips * Apply suggestions from code review Co-authored-by:
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- 11 Oct, 2022 9 commits
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Mathieu Jouffroy authored
* implemented TFCvtModel and TFCvtForImageClassification and modified relevant files, added an exception in convert_tf_weight_name_to_pt_weight_name, added quick testing file to compare with pytorch model * added docstring + testing file in transformers testing suite * added test in testing file, modified docs to pass repo-consistency, passed formatting test * refactoring + passing all test * small refacto, removing unwanted comments * improved testing config * corrected import error * modified acces to pretrained model archive list, to pass tf_test * corrected import structure in init files * modified testing for keras_fit with cpu * correcting PR issues + Refactoring * Refactoring : improving readability and reducing the number of permutations * corrected momentum value + cls_token initialization * removed from_pt as weights were added to the hub * Update tests/models/cvt/test_modeling_tf_cvt.py Co-authored-by: -
Quancore authored
* Added tokenize keyword arguments to feature extraction pipeline * Reverted truncation parameter * Import numpy moved to top
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David Yang authored
* Make cpm tokenization independent of xlnet * Make bert japanese tokenization independent of bert
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Joao Gante authored
🚨 🚨 🚨 TF: Remove `TFWrappedEmbeddings` (breaking: TF embedding initialization updated for encoder-decoder models) (#19263) * added test * correct embedding init * some changes in blenderbot (incomplete) * update blenderbot (diff to be used as reference) * update blenderbot_small * update LED * update marian * update T5 and remove TFWrappedEmbeddings * nullcontext() -> ContextManagers() * fix embedding init -
Ankur Goyal authored
* Implement multiple span support * Address comments * Add tests + fix bugs
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Yih-Dar authored
Co-authored-by: -
Yih-Dar authored
* Fix TFGroupViT CI Co-authored-by: -
Arthur authored
* update feature extractor params * update attention mask handling * fix doc and pipeline test * add warning when skipping test * add whisper translation and transcription test * fix build doc test
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Dimitre Oliveira authored
* Custom TF signature draft * Apply suggestions from code review Co-authored-by:
Dimitre Oliveira <dimitreoliveira@Dimitres-MacBook-Air.local>
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- 10 Oct, 2022 7 commits
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Partho authored
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Partho authored
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Partho authored
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Partho authored
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Partho authored
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Partho authored
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amyeroberts authored
* simplify loop * add featur extractor * add model * start conversion * add dropout * initial commit of test files * copnversion for all models * update processor for correct padding * update feature extraction * update integration test logits match * fmnt: off for the logits * on the fly mel bank * small nit * update test * update tokenizer * nit feature extraction * update * update tokenizer test * adds logit processor and update tokenizer to get supress tokens * style * clean convert * revert to original modeling tf utils * Update * update * nit * clean convert file * update tests and nits * quality * slow generation test * ffn_dim to allow customization * update readme * add to toctreee * start fixing integration tests * update tests and code * fix feature extractor * fix config tests common * update code to fix tests * fix feature exctractor * nit feature extraction * update test for new feature extractor * style * add absrtact * large logits wioth custom decoder input ids * wraap around is otrch available * fix feature extractor * correct logits for whisper small.en * nit * fix encoder_attentino_mask * some fixes * remove unnecessary inputs * nits * add normalizer file * update etst tokenization * fix attention mask not defined * fix generate * remove uncoder attention mask useless * update test modeling whisper * update condfig to add second non supress tokens * nits on feature exrtactor * nit for test tokenizers * update etsts * update tests * update tokenization test * fixup * invalidated hf token. Clean convert openai to whisper * fix logit tests * fixup * Add model to README * Fix doc tests * clean merge * revert toc_tree changes * remove useless LogitProcessor * Update whisper .mdx * update config file doc * update configuration docstring * update test tokenization * update test tokenization * update tokenization whisper Added copied from where needed * update feature extraction * nit test name * style * quality * remove get suppress tokens and update non_speech tokens global variables * Update src/transformers/models/whisper/feature_extraction_whisper.py Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * clean modeling whisper and test Removed the attention mask arguments that are deprecated * fix large test * Add multilingual audio test, and translate test * style * fix larg multilingual test * nits * add copied from for attention layer * remove attention masks in doc * add english normalizer * Update docs/source/en/model_doc/whisper.mdx Co-authored-by:
Arthur Zucker <arthur.zucker@gmail.com> Co-authored-by:
NielsRogge <niels.rogge1@gmail.com> Co-authored-by:
Joao Gante <joao@huggingface.co>
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