* Add support for deepspeed optimizer and HF scheduler
* fix bug
* fix the import
* fix issue with deepspeed scheduler saving for hf optim + hf scheduler scenario
* fix loading of hf scheduler when loading deepspeed checkpoint
* fix import of `DeepSpeedSchedulerWrapper`
* add tests
* add the comment and skip the failing tests
* address comment
* Add Blip2 model in VQA pipeline
* use require_torch_gpu for test_large_model_pt_blip2
* use can_generate in vqa pipeline
* test Blip2ForConditionalGeneration using float16
* remove custom can_generate from Blip2ForConditionalGeneration
* fixing name position_embeddings to object_queries
* [fix] renaming variable and docstring do object queries
* [fix] comment position_embedding to object queries
* [feat] changes from make-fix-copies to keep consistency
* Revert "[feat] changes from make-fix-copies to keep consistency"
This reverts commit 56e3e9ede1d32f7aeefba707ddfaf12c9b4b9e7e.
* [tests] fix wrong expected score
* [fix] wrong assignment causing wrong tensor shapes
* [fix] fixing position_embeddings to object queries to keep consistency (make fix copies)
* [fix] make fix copies, renaming position_embeddings to object_queries
* [fix] positional_embeddingss to object queries, fixes from make fix copies
* [fix] comments frmo make fix copies
* [fix] adding args validation to keep version support
* [fix] adding args validation to keep version support -conditional detr
* [fix] adding args validation to keep version support - maskformer
* [style] make fixup style fixes
* [feat] adding args checking
* [feat] fixcopies and args checking
* make fixup
* make fixup
---------
Co-authored-by: Lorenzobattistela <lorenzobattistela@gmail.com>
* add all
* Revert "Delete .github directory"
This reverts commit 9b0ff7b052e2b20b629a26fb13606b78a42944d1.
* make conversion script backward compatible
* fixup
* more styling
* copy to llama changes
* fix repo consistency
* nits
* document correct classes
* updates
* more fixes
* nits
* update auto mappings
* add readmes
* smallupdates
* llama-code replace with llama_code
* make fixup
* updates to the testsing suite
* fix fast nits
* more small fixes
* fix decode
* fix template processing
* properly reset the normalizer
* nits processor
* tokenization tests pass
* styling
* last tests
* additional nits
* one test is left
* nits
Co-authored-by faabian <faabian@users.noreply.github.com>
* update failing test
* fixup
* remove decode infilling users should handle it on their onw after generation, padding can be a problem
* update
* make test slow and more meaningfull
* fixup
* doc update
* fixup
* Apply suggestions from code review
* add kwargs doc
* tokenizer requires `requires_backend`
* type requires_backends
* CodeLlama instead of LlamaCode
* more name cahnges
* nits
* make doctests happy
* small pipeline nits
* last nit
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* update
* add codellama to toctree
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Correct attention mask dtype
* reformat code
* add a test for boolean mask
* convert test to fast test
* delete unwanted print
* use assertTrue for testing
* properly support Sequence of pretokenizers
* actual fix
* make sure the fix works. Tests are not working for sure!
* hacky way
* add TODO
* update
* add a todo
* nits
* rename test
* nits
* rename test
* add: NumberNormalizer works for integers, floats, common currencies, negative numbers and percentages
* fix: renamed number normalizer class and added normalization to SpeechT5Processor
* fix: restyled with black and ruff, should pass code quality tests
* fix: moved normalization to tokenizer and other small changes to normalizer
* add: test for normalization and changed the existing full tokenizer test
* fix: tokenization tests now pass, made changes to existing tokenization where normalization is covered; added normalize arg to func signature
* fix: changed default normalize setting to False, modified the tests a bit
* fix: added support for comma separated numbers, tokenization on the fly with kwargs and normalizer getter setter funcs
* init commit
* config updated also some modeling
* Processor and Model config combined
* extraction pipeline(upto before spectogram & mel_conditioner) added but not properly tested
* model loading successful!
* feature extractor done!
* FE can now be called from HF
* postprocessing added in fe file
* same as prev commit
* Pop2PianoConfig doc done
* cfg docs slightly changed
* fe docs done
* batched
* batched working!
* temp
* v1
* checking
* trying to go with generate
* with generate and model tests passed
* before rebasing
* .
* tests done docs done remaining others & nits
* nits
* LogMelSpectogram shifted to FeatureExtractor
* is_tf rmeoved from pop2piano/init
* import solved
* tokenization tests added
* minor fixed regarding modeling_pop2piano
* tokenizer changed to only return midi_object and other changes
* Updated paper abstract(Camera-ready version) (#2)
* more comments and nits
* ruff changes
* code quality fix
* sg comments
* t5 change added and rebased
* comments except batching
* batching done
* comments
* small doc fix
* example removed from modeling
* ckpt
* forward it compatible with fe and generation done
* comments
* comments
* code-quality fix(maybe)
* ckpts changed
* doc file changed from mdx to md
* test fixes
* tokenizer test fix
* changes
* nits done main changes remaining
* code modified
* Pop2PianoProcessor added with tests
* other comments
* added Pop2PianoProcessor to dummy_objects
* added require_onnx to modeling file
* changes
* update .md file
* remove extra line in index.md
* back to the main index
* added pop2piano to index
* Added tokenizer.__call__ with valid args and batch_decode and aligned the processor part too
* changes
* added return types to 2 tokenizer methods
* the PR build test might work now
* added backends
* PR build fix
* vocab added
* comments
* refactored vocab into 1 file
* added conversion script
* comments
* essentia version changed in .md
* comments
* more tokenizer tests added
* minor fix
* tests extended for outputs acc check
* small fix
---------
Co-authored-by: Jongho Choi <sweetcocoa@snu.ac.kr>
* a draft version
* v2 integration
* fix
* make it more generic and works for IA3
* add set adapter and multiple adapters support
* fixup
* adapt a bit
* oops
* oops
* oops
* adapt more
* fix
* add more refactor
* now works with model class
* change it to instance method as it causes issues with `jit`.
* add CR
* change method name
* add `add_adapter` method
* clean up
* Update src/transformers/adapters/peft_mixin.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add moe utils
* fixup
* Update src/transformers/adapters/peft_mixin.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* adapt
* oops
* fixup
* add is_peft_available
* remove `requires_backend`
* trainer compatibility
* fixup + docstring
* more details
* trigger CI
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_utils.py
* fixup + is_main_process
* added `save_peft_format` in save_pretrained
* up
* fix nits here and there
* nits here and there.
* docs
* revert `encoding="utf-8"`
* comment
* added slow tests before the PEFT release.
* fixup and nits
* let's be on the safe zone
* added more comments
* v1 docs
* add remaining docs
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* move to `lib_integrations`
* fixup
* this time fixup
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* address final comments
* refactor to use `token`
* add PEFT to DockerFile for slow tests.
* added pipeline support.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* draft changes
* update and add tests
* styling for no
* move test
* path to usable model
* update test
* small update
* update bertbased tokenizers
* don'tuse kwargs for _tokenize
* don'tuse kwargs for _tokenize
* fix copies
* update
* update test for special tokenizers
* fixup
* skip two tests
* remove pdb breakpiont()
* wowo
* rewrite custom tests
* nits
* revert chang in target keys
* fix markup lm
* update documentation of the argument
