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* add position bias head masking if heads pruned * fix pruning function in t5 encoder * make style * make fix-copies * Revert added folder Co-authored-by: Patrick von Platen <[email protected]>
…raining (huggingface#18877) Co-authored-by: Arun Rajaram <[email protected]>
* use tokenizer to output tensor * add preprocessing for decoder_input_ids for bare T5Model * add preprocessing to tf and flax * linting * linting * Update src/transformers/models/t5/modeling_flax_t5.py Co-authored-by: Patrick von Platen <[email protected]> * Update src/transformers/models/t5/modeling_tf_t5.py Co-authored-by: Patrick von Platen <[email protected]> * Update src/transformers/models/t5/modeling_t5.py Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: Patrick von Platen <[email protected]>
…#18898) Co-authored-by: ydshieh <[email protected]>
…face#18871) * Further reduce the number of alls to head for cached models/tokenizers/pipelines * Fix tests * Address review comments
Co-authored-by: ydshieh <[email protected]>
…ity of fixed-length models` (huggingface#18906) * update the PPL for stride 512 * fix 1st strided window size * linting * fix typo * styling
* Simplify code example * Add seed
* add check for scheduled CI * Add check to other CIs Co-authored-by: ydshieh <[email protected]>
* add accelerator.end_training() Some trackers need this to end their runs. * fixup and quality * add space * add space again ?!?
…uggingface#18918) Signed-off-by: Wang, Yi A <[email protected]> Signed-off-by: Wang, Yi A <[email protected]>
* Update TF fine-tuning docs * Fix formatting * Add some section headers so the right sidebar works better * Squiggly it * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/training.mdx Co-authored-by: Sylvain Gugger <[email protected]> * Explain things in the text, not the comments * Make the two dataset creation methods into a list * Move the advice about collation out of a <Tip> * Edits for clarity * Edits for clarity * Edits for clarity * Replace `to_tf_dataset` with `prepare_tf_dataset` in the fine-tuning pages * Restructure the page a little bit * Restructure the page a little bit * Restructure the page a little bit Co-authored-by: Steven Liu <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
…uggingface#18667) * remvoe _create_and_check_torch_fx_tracing defined in specific model test files Co-authored-by: ydshieh <[email protected]>
…ingface#18911) * [DeepSpeed] Fix performance degradation in sharded models * style * polish Co-authored-by: Stas Bekman <[email protected]>
* [WIP] Skeleton of VisualQuestionAnweringPipeline extended to support LayoutLM-like models * Fixup * Use the full encoding * Basic refactoring to DocumentQuestionAnsweringPipeline * Cleanup * Improve args, docs, and implement preprocessing * Integrate OCR * Refactor question_answering pipeline * Use refactored QA code in the document qa pipeline * Fix tests * Some small cleanups * Use a string type annotation for Image.Image * Update encoding with image features * Wire through the basic docs * Handle invalid response * Handle empty word_boxes properly * Docstring fix * Integrate Donut model * Fixup * Incorporate comments * Address comments * Initial incorporation of tests * Address Comments * Change assert to ValueError * Comments * Wrap `score` in float to make it JSON serializable * Incorporate AutoModeLForDocumentQuestionAnswering changes * Fixup * Rename postprocess function * Fix auto import * Applying comments * Improve docs * Remove extra assets and add copyright * Address comments Co-authored-by: Ankur Goyal <[email protected]>
Co-authored-by: ydshieh <[email protected]>
* Fix XLA fp16 and bf16 error checking * Update src/transformers/training_args.py Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* Starts on a list of external deps required for dev I've found that I need to install MeCab manually on my AS Mac. * Generalizes OS nascent dependency list Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* skip some code examples for doctests * make style * fix code snippet formatting * separate code snippet into two blocks
* fix LayoutXLM wrong link in README * fix LayoutXLM worng link in index.mdx
* First draft * Improve conversion script * Make vision encoder work * More improvements * Improve conversion script * Fix quality * Add MultiframeIntegrationTransformer * More improvements * Make MiT output work * Fix quality * Add prompts generator * Add tests * Fix some tests * Fix some more tests * Fix more tests * Improve conversion script * Fix model outputs * Fix more tests * Add XClipProcessor * Use processor in conversion script * Fix integration test * Update README, fix docs * Fix all tests * Add MIT output to XClipOutput * Create better variable names * Rename XClip to XCLIP * Extend conversion script * Add support for large models * Add support for 16 frame models * Add another model' * Fix module issue * Apply suggestions from code review * Add figure to docs * Fix CLIPProcessor issue * Apply suggestions from code review * Delete file * Convert more checkpoints * Convert last checkpoint * Update nielsr to microsoft
* Update TRANSLATING.md Update the contact to @GuggerSylvain * Update docs/TRANSLATING.md Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
…uggingface#18686) * add_ernie * remove Tokenizer in ernie * polish code * format code style * polish code * fix style * update doc * make fix-copies * change model name * change model name * fix dependency * add more copied from * rename ErnieLMHeadModel to ErnieForCausalLM do not expose ErnieLayer update doc * fix * make style * polish code * polish code * fix * fix * fix * fix * fix * final fix Co-authored-by: ydshieh <[email protected]>
…face#18361) * [JAX] Replace all jax.tree_* calls with jax.tree_util.tree_* * fix double tree_util
* NeptuneCallback improvements * After review suggestions and deduplication of initial run * Added volatile checkpoints support due to missing post-rebase commit * Update README per review comments - Remove list formatting - Correct Neptune docs link Co-authored-by: Sabine <[email protected]>
* Fix train_step and test_step, correctly enable CLIP fit test * Stop using get_args on older Python versions * Don't use get_origin either * UnionType is actually even newer, don't use that either * Apply the same fix to test_loss_computation * Just realized I was accidentally skipping a bunch of tests! * Fix test_loss_computation for models without separable labels * Fix scalar losses in test_step and train_step * Stop committing your breakpoints * Fix Swin loss shape * Fix Tapas loss shape * Shape fixes for TAPAS, DeIT, HuBERT and ViTMAE * Add loss computation to TFMobileBertForPreTraining * make fixup and move copied from statement * make fixup and move copied from statement * Correct copied from * Add labels and next_sentence_label inputs to TFMobileBERT * Make sure total_loss is always defined * Update tests/test_modeling_tf_common.py Co-authored-by: amyeroberts <[email protected]> * Fix copied from * Ensure CTC models get labels in tests * Ensure CTC models get labels in tests * Fix tests for vit_mae * Fix tests for vit_mae * Fix tests for vit_mae * Reduce batch size for wav2vec2 testing because it was causing OOM * Skip some TAPAS tests that are failing * Skip a failing HuBERT test * make style * Fix mobilebertforpretraining test * Skip Wav2Vec2 tests that use huge amounts of mem * Skip keras_fit for Wav2Vec2 as well Co-authored-by: amyeroberts <[email protected]>
correct the import statement
* Small replacement - replace `modules_to_not_convert` by `module_to_not_convert` * refactor a bit - changed variables name - now output a list - change error message * make style * add list * make style * change args name Co-authored-by: stas00 <[email protected]> * fix comment * fix typo Co-authored-by: stas00 <[email protected]> * Update src/transformers/modeling_utils.py Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: stas00 <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* Updated test values The image segmentation pipeline tests - tests/pipelines/test_pipelines_image_segmentation.py - were failing after the merging of huggingface#1849 (49e44b2). This was due to the difference in rescaling. Previously the images were rescaled by `image = image / 255`. In the new commit, a `rescale` method was added, and images rescaled using `image = image * scale`. This was known to cause small differences in the processed images (see [PR comment](huggingface#18499 (comment))). Testing locally, changing the `rescale` method to divide by a scale factor (255) resulted in the tests passing. It was therefore decided the test values could be updated, as there was no logic difference between the commits. * Use double quotes, like previous example * Fix up
* Fix test_save_load for TFViTMAEModelTest Co-authored-by: ydshieh <[email protected]>
…face#19034) * Override save() to use the serving signature as the default * Replace int32 with int64 in all our serving signatures * Remember one very important line so as not to break every test at once * Dtype fix for TFLED * dtype fix for shift_tokens_right in general * Dtype fixes in mBART and RAG * Fix dtypes for test_unpack_inputs * More dtype fixes * Yet more mBART + RAG dtype fixes * Yet more mBART + RAG dtype fixes * Add a check that the model actually has a serving method
* init PR * optimize top p and add edge case * styling * style * revert tf and flax test * add edge case test for FLAX and TF * update doc with smallest set sampling for top p * make style
* Fixing OPT fast tokenizer option. * Remove dependency on `pt`. * Move it to GPT2 tokenization tests. * Added a few tests.
* Fix CI for custom tokenizers * Add nightly tests * Run CI, run! * Fix paths * Typos * Fix test
* Enable torchdynamo tests * make style Co-authored-by: ydshieh <[email protected]>
…uggingface#18702) * Adds package and requirement spec output to version check exception It's difficult to understand what package is affected when `got_ver` here comes back None, so output the requirement and the package. The requirement probably contains the package but let's output both for good measure. Non-exhaustive references for this problem aside from my own encounter: * https://stackoverflow.com/questions/70151167/valueerror-got-ver-is-none-when-importing-tensorflow * https://discuss.huggingface.co/t/valueerror-got-ver-is-none/17465 * UKPLab/sentence-transformers#1186 * huggingface#13356 I speculate that the root of the error comes from a conflict of conda-managed and pip-managed Python packages but I've not yet proven this. * Combines version presence check and streamlines exception message See also: huggingface#18702 (comment) Co-authored-by: Stas Bekman <[email protected]>
* Support for ConvNext * Support for Wav2Vec2 * Support for Resnet * Fix small issue in test_modeling_convnext
…P16 input (huggingface#18746) * Adding cast to fp32 in convnext layernorm to prevent rounding errors in the case of fp16 input * Trigger CI
* Tests conditional run * Syntax * Deps * Try early exit * Another way * Test with no tests to run * Test all * Typo * Try this way * With tests to run * Mostly finished * Typo * With a modification in one file only * No change, no tests * Final cleanup * Address review comments
…ngface#19064) * Add CLIP to zero-shot-image-classification * Make mapping private as it's not used for AutoClassing
Co-authored-by: ydshieh <[email protected]>
…e#19013) * resized models that we can actually load * separate embeddings check * add test for embeddings out of bounds * add fake slows
…gface#19039) * added type hints pytorch unispeech * added type hints pytorch MPNet * added type hints nystromformer * resolved copy inconsistencies * make fix-copies Co-authored-by: matt <[email protected]>
* Fix tokenizer load from one file * Add a test * Style Co-authored-by: Lysandre <[email protected]>
…gface#19077) Bumps [mako](https://github.com/sqlalchemy/mako) from 1.2.0 to 1.2.2. - [Release notes](https://github.com/sqlalchemy/mako/releases) - [Changelog](https://github.com/sqlalchemy/mako/blob/main/CHANGES) - [Commits](https://github.com/sqlalchemy/mako/commits) --- updated-dependencies: - dependency-name: mako dependency-type: direct:production ... Signed-off-by: dependabot[bot] <[email protected]> Signed-off-by: dependabot[bot] <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* german autoclass * Update _toctree.yml
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