* fix?

* actual fix

* fixups

* add dataclass to the attention mask converter

* refine testing suite

* make sure there are no overflows

* update the test

* init commit

* attention arch done except rotary emb

* rotary emb done

* text encoder working

* outputs matching

* arch first pass done

* make commands done, tests and docs remaining

* all tests passed, only docs remaining

* docs done

* doc-builder fix

* convert script removed(not relevant)

* minor comments done

* added ckpt conversion script

* tokenizer done

* very minor fix of index.md 2

* mostly make fixup related

* all done except fe and rotary emb

* very small change

* removed unidecode dependency

* style changes

* tokenizer removed require_backends

* added require_inflect to tokenizer tests

* removed VOCAB_FILES in tokenizer test

* inflect dependency removed

* added rotary pos emb cache and simplified the apply method

* style

* little doc change

* more comments

* feature extractor added

* added processor

* auto-regressive config added

* added CLVPConditioningEncoder

* comments done except the test one

* weights added successfull(NOT tested)

* tokenizer fix with numbers

* generate outputs matching

* almost tests passing Integ tests not written

* Integ tests added

* major CUDA error fixed

* docs done

* rebase and multiple fixes

* fixed rebase overwrites

* generate code simplified and tests for AutoRegressive model added

* minor changes

* refectored gpt2 code in clvp file

* weights done and all code refactored

* mostly done except the fast_tokenizer

* doc test fix

* config file's doc fixes

* more config fix

* more comments

* tokenizer comments mostly done

* modeling file mostly refactored and can load modules

* ClvpEncoder tested

* ClvpDecoder, ClvpModel and ClvpForCausalLM tested

* integration and all tests passed

* more fixes

* docs almost done

* ckpt conversion refectored

* style and some failing tests fix

* comments

* temporary output fix but test_assisted_decoding_matches_greedy_search test fails

* majority changes done

* use_cache outputs same now! Along with the asisted_greedy_decoding test fix

* more comments

* more comments

* prepare_inputs_for_generation fixed and _prepare_model_inputs added

* style fix

* clvp.md change

* moved clvpconditionalencoder norms

* add model to new index

* added tokenizer input_ids_with_special_tokens

* small fix

* config mostly done

* added config-tester and changed conversion script

* more comments

* comments

* style fix

* some comments

* tokenizer changed back to prev state

* small commnets

* added output hidden states for the main model

* style fix

* comments

* small change

* revert small change

* .

* Update clvp.md

* Update test_modeling_clvp.py

* :)

* some minor change

* new fixes

* remove to_dict from FE

* update Bark FA2 docs

* update benchmark section

* Update bark.md

* Apply suggestions from code review

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* rephrase

---------

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* add str to enum conversion

* fixup

* Apply suggestions from code review

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add attention_mask and position_ids in assisted model

* fix bug

* fix attention mask

* fix attention_mask

* check assist inputs

* check assist input ids length

* fix assist model type

* set assist attention mask device

* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* fix

* fix

* fix

* fix

* fix

* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* remove failing tests and clean FE files

* remove same similar text from tvlt

* Fix RequestCounter to make it more future-proof

* code quality

* fix

* [test-all] commit

* fix

* [test-all] commit

* [test-all] commit

* fix

* fix

* fix

* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Use editable install

* Full command

fix

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

fix

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* dvclive trainer callback

* style fixes

* dvclive link fixes

* Skip failing cache call tests

* Fixup

fix

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Change thresh

[`CodeLlamaTokenizer`] Nit, update __init__ to make sure the AddedTokens are not normalized because they are special (#27359)

* make sure tokens are properly initialized for codellama slow

* add m ore pretrained models

* style

* test more tokenizers checkpoints

* fix failing DeepSpeed CI tests due to `safetensors` being default

* debug

* remove debug statements

* resolve comments

* Update test_deepspeed.py

* update

* update

* Update deprecated torch.range

* Remove comment

* change handmade attention mask to _prepare_4d_attention_mask

* add flashattention2 support in Bark

* add flashattention2 tests on BarkSemanticModel

* make style

* fix flashattention and tests + make style

* fix memory leak and allow Bark to pass flash attention to sub-models

* make style

* Apply suggestions from code review

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* remove unecessary code from tests + justify overriding

* Update tests/models/bark/test_modeling_bark.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make style

---------

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* translate performance.md

* tranlsate performance.md and big_models.md

* update translation

* update review

fix

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Unused param

* Add index.md for tukish language

* Fix index.md (huggingface/transformers#27088)

* Add 'tr' to additional files

* Update docs/source/tr/_toctree.yml

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update index.md

---------

Co-authored-by: Mert Yanık <mert.yanik@lcwaikiki.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* [MusicGen] Add stereo model

* safe serialization

* Update src/transformers/models/musicgen/modeling_musicgen.py

* split over 2 lines

* fix slow tests on cuda

* fix

* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix example tests from failing

* CHange thresh

move example of benchmarking to legacy

* add audio_utils usage in the FE of SpeechToText

* clean unecessary parameters of AudioSpectrogramTransformer FE

* add audio_utils usage in AST

* add serialization tests and function to FEs

* make style

* remove use_torchaudio and move to_dict to FE

* test audio_utils usage

* make style and fix import (remove torchaudio dependency import)

* fix torch dependency for jax and tensor tests

* fix typo

* clean tests with suggestions

* add lines to test if is_speech_availble is False

* translate model_sharing.md

* translate llm_tutorial.md to chiense

* update wrong translation

* update _torctree.yml

* update typos

* update

* translate the en tokenizer_summary.md to Chinese

* revise WordPiece

* add to source/zh/_toctree.yml

* Allow for scheduler kwargs

* Formatting

* Arguments checks, passing the tests

* Black failed somehow

---------

Co-authored-by: Pierre <pierre@avatarin.com>

* fix bark batching

* make style

* add tests and make style

* `nospeech` instead of `nocaption` for the no speech token

* oups

Update modeling_gpt_bigcode.py

Resolve AttributeError by utilizing device calculation at the start of the forward function (#27347)

This commit addresses the 'NoneType' object AttributeError within the IdeficsModel forward function. Previously, the 'device' attribute was accessed directly from input_ids, resulting in a potential 'NoneType' error. Now, the device is properly calculated at the beginning of the forward function and utilized consistently throughout, ensuring the 'image_hidden_states' are derived from the correct device. This modification enables smoother processing and compatibility, ensuring the correct device attribution for 'image_encoder_embeddings' in the IdeficsModel forward pass.