* [AutoProcessor] Correct AutoProcessor and automatically add processor class
* up
* up
* up
* up
* up
* up
* up
* up
* continue tomorrow
* up
* up
* up
* make processor class private
* fix loop
* Add ElectraForCausalLM and cover some basic tests & need to fix a few tests
* Fix bugs
* make style
* make fix-copies
* Update doc
* Change docstring to markdown format
* Remove redundant update_keys_to_ignore
* Pipeline chunks.
* Batching for Chunking pipelines ?
* Batching for `question-answering` and `zero-shot-cls`.
* Fixing for FNet.
* Making ASR a chunk pipeline.
* Chunking ASR API.
* doc style.
* Fixing ASR test.
* Fixing QA eror (p_mask, padding is 1, not 0).
* Enable both vad and simple chunking.
* Max length for vad.
* remove inference mode, crashing on s2t.
* Revert ChunkPipeline for ASRpipeline.
Too many knobs for simple integration within the pipeline, better stick
to external convenience functions instead, more control to be had,
simpler pipeline and also easier to replace with other things later.
* Drop necessity for PT for these.
* Enabling generators.
* Add mic + cleanup.
* Typo.
* Typo2.
* Remove ASR work, it does not belong in this PR anymore.
* Update src/transformers/pipelines/pt_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Update src/transformers/pipelines/zero_shot_classification.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Adding many comments.
* Doc quality.
* `hidden_states` handling.
* Adding doc.
* Bad rebase.
* Autofixing docs.
* Fixing CRITICAL bug in the new Zerocls pipeline.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* First commit to add MarianMT to ONNX
* Now MarianModel.forward() automatically generates decoder_input_ids, like BartModel.forward()
* Adjusted MarianOnnxConfig.inputs and outputs to work with seq2seq-lm feature
* Style fix
* Added support for other features for already supported models
* Partial support for causal and seq2seq models
* Partial support for causal and seq2seq models
* Add default task for MarianMT ONNX
* Remove automatic creation of decoder_input_ids
* Extend inputs and outputs for MarianMT ONNX config
* Add MarianMT to ONNX unit tests
* Refactor
* OnnxSeq2SeqConfigWithPast to support seq2seq models
* Parameterized the onnx tests
* Restored run_mlm.py
* Restored run_mlm.py
* [WIP] BART update
* BART and MBART
* Add past_key_values and fix dummy decoder inputs
Using a sequence length of 1 in generate_dummy_outputs() produces large discrepancies, presumably due to some hidden optimisations.
* Refactor MarianOnnxConfig to remove custom past_key_values logic
* Fix quality
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Refactor Marian export to account for base changes
* Fix copies
* Implemented suggestions
* Extend support for causal LM
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Implemented suggestions
* Fixed __init__ to resolve conflict with master
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Implemented suggestions
* Fixed __init__ to resolve conflict with master
* Remove commented import
* Remove ONNX model
* Remove redundant class method
* Tidy up imports
* Fix quality
* Refactor dummy input function
* Add copied from statements to Marian config functions
* Remove false copied from comments
* Fix copy from comment
Co-authored-by: Massimiliano Bruni <massimiliano.bruni@hcl.com>
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Implemented suggestions
* Fixed __init__ to resolve conflict with master
* Remove commented import
* add tests
* change post-processor, pre-tokenizer and decoder (can't update decoder)
* update test (remove decoder which doesn't depend on trim and add_prefix)
* just update the post_processor
* fix change
* `trim_offsets` has no influence on `pre_tokenizer`
* remove a test that need some input from the `tokenizers` lib maintainers
* format
* add new test offsets roberta
* polish comments
* add custom `stopping_criteria` and `logits_processor` to `generate`
* add tests for custom `stopping_criteria` and `logits_processor`
* fix typo in RAG
* address reviewer comments
* improve custom logits processor/stopping criteria error message
* fix types in merge function signature
* change default for custom list from `None` to empty list
* fix rag generate
* add string split suggestion
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add a main_input_name attribute to all models
* Fix tests
* Wtf Vs Code?
* Update src/transformers/models/imagegpt/modeling_imagegpt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Style
* Fix copies
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Implement head_mask for Flax BERT and other models copied from BERT
* Remove `from jax._src.nn.functions import sigmoid`
Remove `from jax._src.nn.functions import sigmoid` unintentionally added by IDE
* Remove no more valid copy statement
* Apply patil-suraj's suggestions from code review
* Apply suggestions from the code review
* Update Flax template
* Fix a typo
* Also update template for CausalLM modules
* Initial commit for Keras model cards
* Revert accidental change
* make style
* make style
* make style
* Fix PR comments
* Move repo creation to __init__
* Fixes to README.md creation
* Partial progress for proper card creation on `push_to_hub`
* Proper card creation from `push_to_hub` plus fixes for malformed model cards
* Fixes for model card creation outside the callback
* Adding a model card creation test
* Putting the model card creation test in the right file.
Good job, Matt.
* make style
* Fix model card test temp dir usage
* Fix model card creation when no optimizer present
* Fixes for when training history not present
* Fix accidental edit to test_modeling_common
* Adding support for multiple mask tokens.
- Original implem: https://github.com/huggingface/transformers/pull/10222
Co-authored-by: njafer <naveen.jafer@oracle.com>
* In order to accomodate optionally multimodal models like Perceiver
we add information to the tasks to specify tasks where we know for sure
if we need the tokenizer/feature_extractor or not.
* Adding info in the documentation about multi masks.
+ marked as experimental.
* Add a copy() to prevent overriding the same tensor over and over.
* Fixup.
* Adding small test for multi mask with real values..
Co-authored-by: njafer <naveen.jafer@oracle.com>
* Adding some slow test to check for perceiver at least from a high level.
* Re-enabling fast tests for Perceiver ImageClassification.
* Perceiver might try to run without Tokenizer (Fast doesn't exist) and
with FeatureExtractor some text only pipelines.
* Oops.
* Adding a comment for `update_config_with_model_class`.
* Remove `model_architecture` to get `tiny_config`.
* Finalize rebase.
* Smarter way to handle undefined FastTokenizer.
* Remove old code.
* Addressing some nits.
* Don't instantiate `None`.
- Do not run image-classification pipeline (_CHECKPOINT_FOR_DOC uses the checkpoint for
langage, which cannot load a FeatureExtractor so current logic fails).
- Add a safeguard to not run tests when `tokenizer_class` or
`feature_extractor_class` **are** defined, but cannot be loaded
This happens for Perceiver for the "FastTokenizer" (which doesn't exist
so None) and FeatureExtractor (which does exist but cannot be loaded
because the checkpoint doesn't define one which is reasonable for the
said checkpoint)
- Added `get_vocab` function to `PerceiverTokenizer` since it is used by
`fill-mask` pipeline when the argument `targets` is used to narrow a
subset of possible values.
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
