* Add the support for the fast (rust) implementation of BlenbderbotTokenizer
* Fix a converter and a typo in a doc
* Apply the patil-suraj's suggestion
* (Nitpick) Fast tokenization -> Fast Tokenization in doc
* Apply the SaulLu's suggestion
* Apply Narsil's suggestion to fix test pipelines
* Add encoder_no_repeat_ngram_size according to the Narsil's suggestion
* Revert the last (unnecessary) commit
* Override pipeline config for Blenderbot to allow for larger pos. emb.
* make fix-copies
* Remove n_ctx from configs
* Fix GPTJ and OpenAIGPT, both are acceptable breaking changes as there are no configs such that it breaks
* Remove unecessary n_positions from TFOpenAIGPT
* First draft
* Make tuple output more readable
* Replace assertions by value errors
* Make it possible to predict_with_generate for vision and speech models
* Adapt Seq2SeqTrainer to work with VisionEncoderDecoder/SpeechEncoderDecoder
* Add deprecation warning
* Add copied from statements to vision and speech encoder decoders
* Fix failing test
* Apply @patrickvonplaten's suggestion
* Use reshape instead of view for consistency
* First draft
* Make style & quality
* Improve conversion script
* Add print statement to see actual slice
* Make absolute tolerance smaller
* Fix image classification models
* Add post_process_semantic method
* Disable padding
* Improve conversion script
* Rename to ForSemanticSegmentation, add integration test, remove post_process methods
* Improve docs
* Fix code quality
* Fix feature extractor tests
* Fix tests for image classification model
* Delete file
* Add is_torch_available to feature extractor
* Improve documentation of feature extractor methods
* Apply suggestions from @sgugger's code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply some more suggestions of code review
* Rebase with master
* Fix rebase issues
* Make sure model only outputs hidden states when the user wants to
* Apply suggestions from code review
* Add pad method
* Support padding of 2d images
* Add print statement
* Add print statement
* Move padding method to SegformerFeatureExtractor
* Fix issue
* Add casting of segmentation maps
* Add test for padding
* Add small note about padding
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* unispeech
* add copy from
* remove hubert copy from
* finish for today
* add unispeech-sat
* adapt more
* up
* up
* up
* up
* add modeling
* add tests
* up
* up
* finish
* up
* Apply suggestions from code review
* up
* up
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* up
* up
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Include KerasTensor in allowed types
- This allows propagating symbolic tensors through TFBert models and layers' call(),
which allows converting the subclass models to functional models.
* Style pass
Co-authored-by: Sergio Valcarcel Macua <sergiov@graphcore.ai>
Co-authored-by: matt <rocketknight1@gmail.com>
Add Camembert to models exportable with ONNX
Co-authored-by: Thomas.Chaigneau <thomas.chaigneau@arkea.com>
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>
* Add seq2seq example for QnA on SQuAD Dataset.
* Changes from review - Fixing styling mistakes.
* Added how to example in README, simplified the access to dataset's preprocess function.
* Added tests for the seq2seq QA example.
* Change dataset column name to fix tests.
* Fix test command mistake.
* Add missing argument 'ignore_pad_token_for_loss' from DataTrainingArguments.
* Add missing argument 'num_beams' from DataTrainingArguments.
* Fix processing of output predicted token ids so that tokenizer decode gets appropriate input. Updated assertion conditions on the tests.
