GitLab

Co-authored-by: Johannes <johannes.kolbe@tech.better.team>

Fix typo for llava next docs

* First draft

* Fix tests, add docs

* Improve docstrings

* Fix test

* Address comments

* Address comments

* Remove vocab_size attribute

* Remove batch_size

* Address comment

* Add image processor tests

* Support fx

* Update docstring

* Add support for 34b

* Convert 34b model

* Add integration tests

* Update checkpoints

* Convert vicuna-13b, remove doc tests

* Remove script

* Remove file

* Address comments

* Improve docstrings

* Deprecate vocab_size

* Remove aspect_ratio_setting

* Address comments

* Update READMEs

* Add tips about chat templates

* Fix tests

* Deprecate vocab_size safely

* Update tests

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

* Added SuperPoint docs

* Added tests

* Removed commented part

* Commit to create and fix add_superpoint branch with a new branch

* Fixed dummy_pt_objects

* Committed missing files

* Fixed README.md

* Apply suggestions from code review

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

* Moved ImagePointDescriptionOutput from modeling_outputs.py to modeling_superpoint.py

* Removed AutoModelForKeypointDetection and related stuff

* Fixed inconsistencies in image_processing_superpoint.py

* Moved infer_on_model logic simply in test_inference

* Fixed bugs, added labels to forward method with checks whether it is properly a None value, also added tests about this logic in test_modeling_superpoint.py

* Added tests to SuperPointImageProcessor to ensure that images are properly converted to grayscale

* Removed remaining mentions of MODEL_FOR_KEYPOINT_DETECTION_MAPPING

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fixed from (w, h) to (h, w) as input for tests

* Removed unnecessary condition

* Moved last_hidden_state to be the first returned

* Moved last_hidden_state to be the first returned (bis)

* Moved last_hidden_state to be the first returned (ter)

* Switched image_width and image_height in tests to match recent changes

* Added config as first SuperPointConvBlock init argument

* Reordered README's after merge

* Added missing first config argument to SuperPointConvBlock instantiations

* Removed formatting error

* Added SuperPoint to README's de, pt-br, ru, te and vi

* Checked out README_fr.md

* Fixed README_fr.md

* Test fix README_fr.md

* Test fix README_fr.md

* Last make fix-copies !

* Updated checkpoint path

* Removed unused SuperPoint doc

* Added missing image

* Update src/transformers/models/superpoint/modeling_superpoint.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Removed unnecessary import

* Update src/transformers/models/superpoint/modeling_superpoint.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Added SuperPoint to _toctree.yml

---------
Co-authored-by: steven <steven.bucaillle@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Steven Bucaille <steven.bucaille@buawei.com>

* first modeling code

* make repository

* still WIP

* update model

* add tests

* add latest change

* clean docstrings and copied from

* update docstrings md and readme

* correct chroma function

* correct copied from and remove unreleated test

* add doc to toctree

* correct imports

* add convert script to notdoctested

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

* correct get_uncoditional_inputs docstrings

* modify README according to SANCHIT feedback

* add chroma to audio utils

* clean librosa and torchaudio hard dependencies

* fix FE

* refactor audio decoder -> audio encoder for consistency with previous musicgen

* refactor conditional -> encoder

* modify sampling rate logics

* modify license at the beginning

* refactor all_self_attns->all_attentions

* remove ignore copy from causallm generate

* add copied from for from_sub_models

* fix make copies

* add warning if audio is truncated

* add copied from where relevant

* remove artefact

* fix convert script

* fix torchaudio and FE

* modify chroma method according to feedback-> better naming

* refactor input_values->input_features

* refactor input_values->input_features and fix import fe

* add input_features to docstrigs

* correct inputs_embeds logics

* remove dtype conversion

* refactor _prepare_conditional_hidden_states_kwargs_for_generation ->_prepare_encoder_hidden_states_kwargs_for_generation

* change warning for chroma length

* Update src/transformers/models/musicgen_melody/convert_musicgen_melody_transformers.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* change way to save wav, using soundfile

* correct docs and change to soundfile

* fix import

* fix init proj layers

* remove line breaks from md

* fix issue with docstrings

* add FE suggestions

* improve is in logics and remove useless imports

* remove custom from_pretrained

* simplify docstring code

* add suggestions for modeling tests

* make style

* update converting script with sanity check

* remove encoder attention mask from conditional generation

* replace musicgen melody checkpoints with official orga

* rename ylacombe->facebook in checkpoints

* fix copies

* remove unecessary warning

* add shape in code docstrings

* add files to slow doc tests

* fix md bug and add md to not_tested

* make fix-copies

* fix hidden states test and batching

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

* Cohere Model Release (#1)

Cohere Model Release

* Remove unnecessary files and code (#2)

Some cleanup

* Delete cohere-model directory (#3)

* Make Fix (#5)

* Pr fixes (#6)

* fixes for pr

* pr fixes for the format

* pr fixes for the format

* src/transformers/models/auto/tokenization_auto.py

* Tokenizer test (#8)

* tokenizer test

* format fix

* Adding Docs and other minor changes (#7)

* Add modeling tests (#9)

* Smol Fix (#11)

* tokenization tests are fixed

* format fixes

* fix pr doc tests

* fix pr doc tests

* fix pr doc tests

* fix pr style check

* small changes in cohere.md

* FIX: Address final comments for transformers integration (#13)

* fix modeling final nits and add proper test file

* for now leave empty tests

* add integration test

* push new test

* fix modeling cohere (#14)

* Update chat templates to use the new API (#15)

---------
Co-authored-by: ahmetustun <ahmetustun89@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Added pytests for pvt-v2, all passed

* Added pvt_v2 to docs/source/end/model_doc

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Reverted batch eval changes for PR

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat. Added additional type support for image size in config

* Fixed config backbone compat

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Reverted batch eval changes for PR

* Updated index.md

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat

* Ran fix-copies

* Fixed PvtV2Backbone tests

* Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py

* Fixed backbone stuff and fixed tests: all passing

* Ran make fixup

* Made modifications for code checks

* Remove ONNX config from configuration_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use explicit image size dict in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Make image_size optional in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove _ntuple use in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove reference to fp16_enabled

* Model modules now take config as first argument even when not used

* Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"

* All LayerNorm now instantiates with config.layer_norm_eps

* Added docstring for depth-wise conv layer

* PvtV2Config now only takes Union[int, Tuple[int, int]] for image size

* Refactored PVTv2 in prep for gradient checkpointing

* Gradient checkpointing ready to test

* Removed override of _set_gradient_checkpointing

* Cleaned out old code

* Applied code fixup

* Applied code fixup

* Began debug of pvt_v2 tests

* Leave handling of num_labels to base pretrained config class

* Deactivated gradient checkpointing tests until it is fixed

* Removed PvtV2ImageProcessor which duped PvtImageProcessor

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Added pvt_v2 to docs/source/end/model_doc

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Reverted batch eval changes for PR

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat. Added additional type support for image size in config

* Fixed config backbone compat

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Reverted batch eval changes for PR

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat

* Ran fix-copies

* Fixed PvtV2Backbone tests

* Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py

* Fixed backbone stuff and fixed tests: all passing

* Ran make fixup

* Made modifications for code checks

* Remove ONNX config from configuration_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use explicit image size dict in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Make image_size optional in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove _ntuple use in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove reference to fp16_enabled

* Model modules now take config as first argument even when not used

* Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"

* All LayerNorm now instantiates with config.layer_norm_eps

* Added docstring for depth-wise conv layer

* PvtV2Config now only takes Union[int, Tuple[int, int]] for image size

* Refactored PVTv2 in prep for gradient checkpointing

* Gradient checkpointing ready to test

* Removed override of _set_gradient_checkpointing

* Cleaned out old code

* Applied code fixup

* Applied code fixup

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Ran fix-copies and fixup. All checks passed

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Reverted batch eval changes for PR

* Fixed config docstring. Added channels property

* Fixed config backbone compat

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Ran fix-copies and fixup. All checks passed

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Fixed config backbone compat

* Ran fix-copies

* Began debug of pvt_v2 tests

* Leave handling of num_labels to base pretrained config class

* Deactivated gradient checkpointing tests until it is fixed

* Removed PvtV2ImageProcessor which duped PvtImageProcessor

* Fixed issue from rebase

* Fixed issue from rebase

* Set tests for gradient checkpointing to skip those using reentrant since it isn't supported

* Fixed issue from rebase

* Fixed issue from rebase

* Changed model name in docs

* Removed duplicate PvtV2Backbone

* Work around type switching issue in tests

* Fix model name in config comments

* Update docs/source/en/model_doc/pvt_v2.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Changed name of variable from 'attn_reduce' to 'sr_type'

* Changed name of variable from 'attn_reduce' to 'sr_type'

* Changed from using 'sr_type' to 'linear_attention' for clarity

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Removed old code

* Changed from using 'sr_type' to 'linear_attention' for clarity

* Fixed Class names to be more descriptive

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Removed outdated code

* Moved paper abstract to single line in pvt_v2.md

* Added usage tips to pvt_v2.md

* Simplified module inits by passing layer_idx

* Fixed typing for hidden_act in PvtV2Config

* Removed unusued import

* Add pvt_v2 to docs/source/en/_toctree.yml

* Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.

* Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Move function parameters to single line
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Update year of copyright to 2024
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

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

* Updated sr_ratio to be more explicit spatial_reduction_ratio

* Removed excess type hints in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Move params to single line in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Removed needless comment in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update copyright date in pvt_v2.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Moved params to single line in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Updated copyright date in configuration_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Cleaned comments in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Renamed spatial_reduction Conv2D operation

* Revert "Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
"

This reverts commit c4a04416dde8f3475ab405d1feb368600e0f8538.

* Updated conversion script to reflect module name change

* Deprecated reshape_last_stage option in config

* Removed unused imports

* Code formatting

* Fixed outdated decorators on test_inference_fp16

* Added "Copied from" comments in test_modeling_pvt_v2.py

* Fixed import listing

* Updated model name

* Force empty commit for PR refresh

* Fixed linting issue

* Removed # Copied from comments

* Added PVTv2 to README_fr.md

* Ran make fix-copies

* Replace all FoamoftheSea hub references with OpenGVLab

* Fixed out_indices and out_features logic in configuration_pvt_v2.py

* Made ImageNet weight conversion verification optional in convert_pvt_v2_to_pytorch.py

* Ran code fixup

* Fixed order of parent classes in PvtV2Config to fix the to_dict method override

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

fix fuyu docs

Fixed broken link for Resources -> Token Classification -> Finetuning BERT for named-entity

* post merge update

* nit

* oups

* add accelerate docs

* Apply suggestions from code review
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* Update starcoder2.md

* add correct generation

---------
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* initial-commit

* start cleaning

* small nits

* small nits

* current updates

* add kernels

* small refactoring little step

* add comments

* styling

* nit

* nits

* Style

* Small changes

* Push dummy mambda simple slow

* nit

* Use original names

* Use original names and remove norm

* Updates for inference params

* Style nd updates

* nits

* Match logits

* Add a test

* Add expected generated text

* nits doc, imports and styling

* style

* oups

* dont install kernels, invite users to install the required kernels

* let use use the original packages

* styling

* nits

* fix some copieds

* update doc

* fix-copies

* styling done

* nits

* fix import check

* run but wrong cuda ress

* mamba CUDA works :)

* fix the fast path

* config naming nits

* conversion script is not required at this stage

* finish fixing the fast path: generation make sense now!

* nit

* Let's start working on the CIs

* style

* better style

* more nits

* test nit

* quick fix for now

* nits

* nit

* nit

* nit

* nits

* update test rest

* fixup

* update test

* nit

* some fixes

* nits

* update test values

* fix styling

* nit

* support peft

* integrations tests require torchg

* also add slow markers

* styling

* chose forward wisely

* nits

* update tests

* fix gradient checkpointing

* fixup

* nit

* fix doc

* check copies

* fix the docstring

* fix some more tests

* style

* fix beam search

* add init schene

* update

* nit

* fix

* fixup the doc

* fix the doc

* fixup

* tentative update but slow is no longer good

* nit

* should we always use float32?

* nits

* revert wrong changes

* res in float32

* cleanup

* skip fmt for now

* update generation values

* update test values running original model

* fixup

* update tests + rename inference_params to cache_params + make sure training does not use cache_params

* small nits

* more nits

* fix final CIs

* style

* nit doc

* I hope final doc nits

* nit

* 🫠

* final touch!

* fix torch import

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Apply suggestions from code review

* fix fix and fix

* fix base model prefix!

* nit

* Update src/transformers/models/mamba/__init__.py

* Update docs/source/en/model_doc/mamba.md
Co-authored-by: Lysandre Debut <hi@lysand.re>

* nit

---------
Co-authored-by: Lysandre Debut <hi@lysand.re>

* First draft

* More improvements

* More improvements

* More fixes

* Fix copies

* More improvements

* More fixes

* More improvements

* Convert checkpoint

* More improvements, set up tests

* Fix more tests

* Add UdopModel

* More improvements

* Fix equivalence test

* More fixes

* Redesign model

* Extend conversion script

* Use real inputs for conversion script

* Add image processor

* Improve conversion script

* Add UdopTokenizer

* Add fast tokenizer

* Add converter

* Update README's

* Add processor

* Add fully fledged tokenizer

* Add fast tokenizer

* Use processor in conversion script

* Add tokenizer tests

* Fix one more test

* Fix more tests

* Fix tokenizer tests

* Enable fast tokenizer tests

* Fix more tests

* Fix additional_special_tokens of fast tokenizer

* Fix tokenizer tests

* Fix more tests

* Fix equivalence test

* Rename image to pixel_values

* Rename seg_data to bbox

* More renamings

* Remove vis_special_token

* More improvements

* Add docs

* Fix copied from

* Update slow tokenizer

* Update fast tokenizer design

* Make text input optional

* Add first draft of processor tests

* Fix more processor tests

* Fix decoder_start_token_id

* Fix test_initialization

* Add integration test

* More improvements

* Improve processor, add test

* Add more copied from

* Add more copied from

* Add more copied from

* Add more copied from

* Remove print statement

* Update README and auto mapping

* Delete files

* Delete another file

* Remove code

* Fix test

* Fix docs

* Remove asserts

* Add doc tests

* Include UDOP in exotic model tests

* Add expected tesseract decodings

* Add sentencepiece

* Use same design as T5

* Add UdopEncoderModel

* Add UdopEncoderModel to tests

* More fixes

* Fix fast tokenizer

* Fix one more test

* Remove parallelisable attribute

* Fix copies

* Remove legacy file

* Copy from T5Tokenizer

* Fix rebase

* More fixes, copy from T5

* More fixes

* Fix init

* Use ArthurZ/udop for tests

* Make all model tests pass

* Remove UdopForConditionalGeneration from auto mapping

* Fix more tests

* fixups

* more fixups

* fix the tokenizers

* remove un-necessary changes

* nits

* nits

* replace truncate_sequences_boxes with truncate_sequences for fix-copies

* nit current path

* add a test for input ids

* ids that we should get taken from c9f7a32f57440d90ff79890270d376a1cc0acb68

* nits converting

* nits

* apply ruff

* nits

* nits

* style

* fix slow order of addition

* fix udop fast range as well

* fixup

* nits

* Add docstrings

* Fix gradient checkpointing

* Update code examples

* Skip tests

* Update integration test

* Address comment

* Make fixup

* Remove extra ids from tokenizer

* Skip test

* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update year

* Address comment

* Address more comments

* Address comments

* Add copied from

* Update CI

* Rename script

* Update model id

* Add AddedToken, skip tests

* Update CI

* Fix doc tests

* Do not use Tesseract for the doc tests

* Remove kwargs

* Add original inputs

* Update casting

* Fix doc test

* Update question

* Update question

* Use LayoutLMv3ImageProcessor

* Update organization

* Improve docs

* Update forward signature

* Make images optional

* Remove deprecated device argument

* Add comment, add add_prefix_space

* More improvements

* Remove kwargs

---------
Co-authored-by: ArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Copy model

* changes

* misc

* fixes

* add embed and residual dropout (#30)

* misc

* remove rms norm and gated MLP

* remove copied mentions where its not a copy anymore

* remove unused _shape

* copied from mistral instead

* fix copies

* fix copies

* add not doctested

* fix

* fix copyright

* Update docs/source/en/model_doc/starcoder2.md
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* Update src/transformers/models/starcoder2/configuration_starcoder2.py
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* Update src/transformers/models/starcoder2/configuration_starcoder2.py
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* fix doc

* revert some changes

* add fa2 tests

* fix styling nit

* fix

* push dummy docs

---------
Co-authored-by: Joel Lamy-Poirier <joel.lamy-poirier@servicenow.com>
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
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* First commit

* Improvements

* More improvements

* Converted original checkpoint to HF checkpoint

* Fix style

* Fixed forward

* More improvements

* More improvements

* Update src/transformers/models/seggpt/modeling_seggpt.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Remove asserts

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* Changed model name to camel case

* Improve forward doc

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* More improvements

* Fix copies

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* Make SegGptImageProcessor more flexible

* Added few-shot test

* Fix style

* Update READMEs and docs

* Update READMEs

* Make inputs required

* Add SegGptForImageSegmentation

* Make tests pass

* Rename to out_indicies

* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Fixed naming convention

* Copying SegGptMlp from modeling_sam.py

* Some minor improvements

* Remove mlp_ratio

* Fix docstrings

* Fixed docstring match

* Objects defined before use

* Storing only patch_size and beta for SegGptLoss

* removed _prepare_inputs method

* Removed modified from headers

* Renamed to output_indicies

* Removed unnecessary einsums

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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Fixing issues

* Raise error as soon as possible

* More fixes

* Fix merge

* Added palette to SegGptImageProcessor

* Fixed typo

* Fixed shape typo

* Added permute before doing palette to class mapping

* Fixed style

* Fixed and added tests

* Fixed docstrings

* Matching SegFormer API for post_processing_semantic_segmentation

* Fixed copies

* Fixed SegGptImageProcessor to handle both binary and RGB masks

* Updated docstrings of SegGptImageProcessor

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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Update tests/models/seggpt/test_image_processing_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Object definitions above & fix style

* Renamed output_indices to intermediate_feature_indices

* Removed unnecessary check on bool_masked_pos

* Loss first in the outputs

* Added validation for do_normalize

* Improved SegGptImageProcessor and added new tests

* Added comment

* Added docstrings to SegGptLoss

* Reimplemented ensemble condition logic in SegGptEncoder

* Update src/transformers/models/seggpt/__init__.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Update src/transformers/models/seggpt/convert_seggpt_to_hf.py
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* Update src/transformers/models/seggpt/configuration_seggpt.py
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* Updated docstrings to use post_process_semantic_segmentation

* Fixed typo on docstrings

* moved pixel values test to test_image_processing_seggpt

* Addressed comments

* Update src/transformers/models/seggpt/configuration_seggpt.py
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* Update src/transformers/models/seggpt/image_processing_seggpt.py
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* Update src/transformers/models/seggpt/configuration_seggpt.py
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* Update src/transformers/models/seggpt/modeling_seggpt.py
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* Updated docstrings for SegGptLoss

* Address comments

* Added SegGpt example to model docs

* Update src/transformers/models/seggpt/modeling_seggpt.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* moved patchify and unpatchify

* Rename checkpoint

* Renamed intermediate_features to intermediate_hidden_states for consistency

* Update src/transformers/models/seggpt/configuration_seggpt.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Replaced post_process_masks for post_process_semantic_segmentation in the docs

---------
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Niels <niels.rogge1@gmail.com>
Co-authored-by: Eduardo Pacheco <eduardo.pacheco@limehome.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* [Pix2struct] Simplify generation (#22527)

* Add model to doc tests

* Remove generate and replace by prepare_inputs_for_generation

* More fixes

* Remove print statements

* Update integration tests

* Fix generate

* Remove model from auto mapping

* Use auto processor

* Fix integration tests

* Fix test

* Add inference code snippet

* Remove is_encoder_decoder

* Update docs

* Remove notebook link

* Release: v4.28.0

* Revert (for now) the change on `Deta` in #22437 (#22750)

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

* Patch release: v4.28.1

* update zh chat template.

* Update docs/source/zh/chat_templating.md
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* Update docs/source/zh/_toctree.yml
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* Update docs/source/zh/chat_templating.md
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* Update docs/source/zh/chat_templating.md
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* Update docs/source/zh/chat_templating.md
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* Update docs/source/zh/chat_templating.md
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* Update docs/source/zh/chat_templating.md
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* Update docs/source/zh/chat_templating.md
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---------
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Michael <haifeng.yao@daocloud.io>

* update model doc qwen2

* Update docs/source/en/model_doc/qwen2.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

---------
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Improve docs

* Improve chat template

* inital commit

* update

* update conversion checkpoint

* update conversion script

* nits

* some fixes

* nits

* merge

* fix permute

* nits

* fix

* nits

* nits

* nits

* fix rope

* fix both rope

* nites

* style

* make sure flax works

* fix flax init code

* fix foward

* nits

* print flax generation out

* current code

* nits

* SIIIIIIIIIIIIIIIIIII

* update

* add new tokenizer

* correct fast tokenizer

* fix conversion

* more comments

* fix modeling and conversion

* nits and nits

* nits testing

* add some tokenization tests

* add some edge cases

* add slow tests and fix them

* fixup

* fix copies for modeling

* fix copies

* add 7B slow tests

* fix

* fix

* fix tests

* make tokenizer cis go green

* styling

* last tokenizer nits

* update jax tests

* fix flax for 7b

* add jit testing 🤗



* cleanups

* isolated nit, inv_freq for rotary_emb.inv_freq

* propagate to jax

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* adjust test

* fix conversion script

* change name

* correct file names

* update conversion script

* Fix bos and eos token ids in the model configuration (#3)

* update modelling

* update conversion script

* add static cache for gemma

* fix sdpa generate

* fix batched

* multiple fixes

* fix FA2

* final fix

* Rename a few missing strings and filenames (#4)

* merge with upstream main

* fix copies

* fix copies

* fix fixup

* fix fixup

* fix

* fix

* final tests

* fix fx gemma tests

* fix fx bf16/fp16 tests

* update slow fx tests

* fx slow tests: one logits, one generation

* move jit test standalone

* Apply suggestions from code review

* nits

* tokenizer updates

* more tokenization updates: custom GemmaSentencepieceExtrator

* style

* Update src/transformers/cache_utils.py

* Update src/transformers/models/gemma/__init__.py

* Update tests/models/gemma/test_modeling_flax_gemma.py

* small nits

* style

* update tokenization test

* fix the rotary embedding

* with style

* fix slow tests

* WARNING this commit might be very important for precisions

* Update tests/models/gemma/test_modeling_flax_gemma.py

* Update src/transformers/models/gemma/configuration_gemma.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Update src/transformers/models/gemma/modeling_flax_gemma.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* small nits here and there!

* forgotten nit

* remove on the fly computation of inv_freq

* revert previous change, let's be safe and for now re-compute freq cis to make sure it's in float

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py
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* Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_flax_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_tokenization_gemma.py
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* Update tests/models/gemma/test_tokenization_gemma.py
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* Update tests/models/gemma/test_tokenization_gemma.py
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* Update tests/models/gemma/test_tokenization_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
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* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* nit conversion script link

* fix some tests

* add not doctest and pr doctest

* repo consistency

* fix last CIs 🚀



* update all readmes

---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Add resource

* Add more resources

* Add resources

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove mention

* Remove pipeline tags

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

* Script & Manual edition

* Update

* First draft

* Add CLIPForImageClassification

* Remove scripts

* Fix doctests

* Add `StableLM`

* fix(model): re-create from `huggingface-cli add-new-model-like persimmon`

* fix: re-add changes to address comments

* fix(readme): add links to paper

* fix(tokenization_auto): remove `GPTNeoXTokenizerFastFast` ref

* fix(tests): re-add `@slow` decorator to integration tests

* fix(tests): import slow...

* fix(readme_hd): remove whitespace edit

* fix(tokenizer): auto tokenizer tuple

* skip doctests for `modeling_stablelm`

Add language identifiers to code blocks

* Fix model documentation links in attention.md

* Fix external link syntax

* Fix target anchor names of section links

* Fix copyright statement comments

* Fix documentation headings

* This is a test commit

* testing commit

* final commit with some changes

* Removed copy statement

* Fixed formatting issues

* Fixed error added past_key_values in the forward method

* Fixed a trailing whitespace. Damn the formatting rules are strict

* Added the copy statement

* Fix typos and grammar mistakes in docs and examples

* Fix typos in docstrings and comments

* Fix spelling of `tokenizer` in model tests

* Remove erroneous spaces in decorators

* Remove extra spaces in Markdown link texts

* Adding [T5/MT5/UMT5]ForTokenClassification

* Add auto mappings for T5ForTokenClassification and variants

* Adding ForTokenClassification to the list of models

* Adding attention_mask param to the T5ForTokenClassification test

* Remove outdated comment in test

* Adding EncoderOnly and Token Classification tests for MT5 and UMT5

* Fix typo in umt5 string

* Add tests for all the existing MT5 models

* Fix wrong comment in dependency_versions_table

* Reverting change to common test for _keys_to_ignore_on_load_missing

The test is correctly picking up redundant keys in _keys_to_ignore_on_load_missing.

* Removing _keys_to_ignore_on_missing from MT5 since the key is not used in the model

* Add fix-copies to MT5ModelTest

* direct copy from llama work

* mistral modules forward pass working

* flax mistral forward pass with sliding window

* added tests

* added layer collection approach

* Revert "added layer collection approach"

This reverts commit 0e2905bf2236ec323163fc1a9f0c016b21aa8b8f.

* Revert "Revert "added layer collection approach""

This reverts commit fb17b6187ac5d16da7c461e1130514dc3d137a43.

* fixed attention outputs

* added mistral to init and auto

* fixed import name

* fixed layernorm weight dtype

* freeze initialized weights

* make sure conversion consideres bfloat16

* added backend

* added docstrings

* added cache

* fixed sliding window causal mask

* passes cache tests

* passed all tests

* applied make style

* removed commented out code

* applied fix-copies ignored other model changes

* applied make fix-copies

* removed unused functions

* passed generation integration test

* slow tests pass

* fixed slow tests

* changed default dtype from jax.numpy.float32 to float32 for docstring check

* skip cache test  for FlaxMistralForSequenceClassification since if pad_token_id in input_ids it doesn't score previous input_ids

* updated checkpoint since from_pt not included

* applied black style

* removed unused args

* Applied styling and fixup

* changed checkpoint for doc back

* fixed rf after adding it to hf hub

* Add dummy ckpt

* applied styling

* added tokenizer to new ckpt

* fixed slice format

* fix init and slice

* changed ref for placeholder TODO

* added copies from Llama

* applied styling

* applied fix-copies

* fixed docs

* update weight dtype reconversion for sharded weights

* removed Nullable input ids

* Removed unnecessary output attentions in Module

* added embedding weight initialziation

* removed unused past_key_values

* fixed deterministic

* Fixed RMS Norm and added copied from

* removed input_embeds

* applied make style

* removed nullable input ids from sequence classification model

* added copied from GPTJ

* added copied from Llama on FlaxMistralDecoderLayer

* added copied from to FlaxMistralPreTrainedModel methods

* fix test deprecation warning

* freeze gpt neox random_params and fix copies

* applied make style

* fixed doc issue

* skipped docstring test to allign # copied from

* applied make style

* removed FlaxMistralForSequenceClassification

* removed unused padding_idx

* removed more sequence classification

* removed sequence classification

* applied styling and consistency

* added copied from in tests

* removed sequence classification test logic

* applied styling

* applied make style

* removed freeze and fixed copies

* undo test change

* changed repeat_kv to tile

* fixed to key value groups

* updated copyright year

* split casual_mask

* empty to rerun failed pt_flax_equivalence test FlaxWav2Vec2ModelTest

* went back to 2023 for tests_pr_documentation_tests

* went back to 2024

* changed tile to repeat

* applied make style

* empty for retry on Wav2Vec2

* [Whisper] Make tokenizer normalization public

* add to docs

* [Docs] Fix Typo in English CLIP model_doc

* [Docs] Fix Typo in Japanese CLIP model_doc

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* Add docs

* Remove file

* Add copied from

* Address comments

* Address comments

* Address comments

* Fix style

* Update docs

* Convert all checkpoints, add integration test

* Rename checkpoints

* Add pretrained backbone attributes

* Fix default config

* Address comment

* Add figure to docs

* Fix bug thanks to @xenova

* Update conversion script

* Fix integration test

Co-authored-by: Pashmina Cameron <11311835+pashminacameron@users.noreply.github.com>

First draft

* first commit

* correct default value non causal

* update config and modeling code

* update converting checkpoint

* clean modeling and fix tests

* make style

* add new config parameters to docstring

* fix copied from statements

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* make position_embeddings_type docstrings clearer

* clean converting script

* remove function not used

* clean modeling file

* apply suggestion for test file + add convert script to not_doctested

* modify tests according to review - cleaner logic and more tests

* Apply nit suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add checker of valid position embeddings type

* instantiate new layer norm layer with the right eps

* fix freeze_feature_encoder since it can be None in some cases

* add test same output in convert script

* restore wav2vec2conformer and add new model

* create processor and FE + clean

* add new model code

* fix convert script and set default config parameters

* correct model id paths

* make style

* make fix-copies and cleaning files

* fix copied from statements

* complete .md and fixe copies

* clean convert script argument defaults

* fix config parameters docstrings

* fix config docstring

* add copied from and enrich FE tests

* fix copied from and repo-consistency

* add autotokenizer

* make test input length shorter and change docstring code

* fix docstrings and copied from

* add add_adapter to ASR training example

* make testing of adapters more robust

* adapt to multi adapter layers

* refactor input_values->input_features and remove w2v2-bert feature extractor

* remove pretraining model

* remove depreciated features and useless lines

* add copied from and ignore statements to modeling tests

* remove pretraining model #2

* change import in convert script

* change default in convert script

* update readme and remove useless line

* Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* refactor BERT to Bert for consistency

* remove useless ignore copy statement

* add persistent to buffer in rotary

* add eps in LayerNorm init and remove copied from

* add adapter activation parameters and add copied from statements

* Fix copied statements and add unitest.skip reasons

* add copied statement in test_processor

* refactor processor

* make style

* replace numpy random by torch rand

* remove expected output CTC

* improve converting script with processor class

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* remove gumbel class

* remove tests related to previously deleted class

* Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* correct typos

* remove uused parameters

* update processor to takes both text and audio

* update checkpoints

* update expected output and add ctc expected output

* add label_attention_mask

* replace pt with np in processor tests

* fix typo

* revert to behaviour with labels_attention_mask

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

* add config, modeling, and tokenization

* add auto and init

* update readme

* update readme

* update team name

* fixup

* fixup

* update config

* update code style

* update for fixup

* update for fixup

* update for fixup

* update for testing

* update for testing

* fix bug for config and tokenization

* fix bug for bos token

* not doctest

* debug tokenizer

* not doctest

* debug tokenization

* debug init for tokenizer

* fix style

* update init

* delete if in token auto

* add tokenizer doc

* add tokenizer in init

* Update dummy_tokenizers_objects.py

* update

* update

* debug

* Update tokenization_qwen2.py

* debug

* Update convert_slow_tokenizer.py

* add copies

* add copied from and make style

* update files map

* update test

* fix style

* fix merge reading and update tests

* fix tests

* fix tests

* fix style

* debug a variable in readme

* Update src/transformers/models/qwen2/configuration_qwen2.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* update test and copied from

* fix style

* update qwen2 tokenization  and tests

* Update tokenization_qwen2.py

* delete the copied from after property

* fix style

* update tests

* update tests

* add copied from

* fix bugs

* update doc

* add warning for sliding window attention

* update qwen2 tokenization

* fix style

* Update src/transformers/models/qwen2/modeling_qwen2.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix tokenizer fast

---------
Co-authored-by: Ren Xuancheng <jklj077@users.noreply.github.com>
Co-authored-by: renxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix(phi): Phi does not use softmax_scale in Flash-Attention.

* chore(docs): Update Phi docs.