GitLab

* Remove ConversationalPipeline and Conversation object, as they have been deprecated for some time and are due for removal

* Update not-doctested.txt

* Fix JA and ZH docs

* Fix JA and ZH docs some more

* Fix JA and ZH docs some more

* Enable load HF or tim backbone checkpoints

* Fix up

* Fix test - pass in proper out_indices

* Update docs

* Fix tvp tests

* Fix doc examples

* Fix doc examples

* Try to resolve DPT backbone param init

* Don't conditionally set to None

* Add condition based on whether backbone is defined

* Address review comments

SpeechBrain usage has changed

Switch from hf_hub_url to hf_hub_download in remaining occurences

* doc: add info about wav2vec2 bert in older wav2vec2 models.

* apply suggestions from review.

* forward contrib credits from review

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

* deprecate blip

* mention deprecation on docs

* add tokenizer_summary to es/_toctree.yml

* add tokenizer_summary to es/

* fix link to Transformes XL in en/

* translate until Subword tokenization section

* fix GPT link in en/

* fix other GPT link in en/

* fix typo in en/

* translate the doc

* run make fixup

* Remove .md in Transformer XL link

* fix some link issues in es/

* fix typo

Update index.md - Contents = Contenu

French typo -
Contents = Contenu

* add qwen2 gguf support

* Update docs

* fix qwen2 tokenizer

* add qwen2 gguf test

* fix typo in qwen2 gguf test

* format code

* Remove mistral, clarify the error message

* format code

* add typing and update docstring

* Initial setup

* Metrics

* Overfit on two batches

* Train 40 epochs

* Memory leak debugging

* Trainer fine-tuning

* Draft

* Fixup

* Trained end-to-end

* Add requirements

* Rewrite evaluator

* nits

* Add readme

* Add instance-segmentation to the table

* Support void masks

* Remove sh

* Update docs

* Add pytorch test

* Add accelerate test

* Update examples/pytorch/instance-segmentation/README.md

* Update examples/pytorch/instance-segmentation/run_instance_segmentation.py

* Update examples/pytorch/instance-segmentation/run_instance_segmentation_no_trainer.py

* Update examples/pytorch/instance-segmentation/run_instance_segmentation_no_trainer.py

* Update examples/pytorch/instance-segmentation/run_instance_segmentation.py

* Fix consistency oneformer

* Fix imports

* Fix imports sort

* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update examples/pytorch/instance-segmentation/run_instance_segmentation.py
Co-authored-by: Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com>

* Add resources to docs

* Update examples/pytorch/instance-segmentation/README.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update examples/pytorch/instance-segmentation/README.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove explicit model_type argument

* Fix tests

* Update readme

* Note about other models

---------
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Implement streaming run in ReAct agents
* Allow additional imports in code agents
* Python interpreter: support classes and exceptions, fixes

`mask` variable is not defined. probably a writing mistake. it should be `segmentation_map`. `segmentation_map` should be a `1` channel image rather than `RGB`.
[on a different note, the `mask_url` is the same as `raw_image`. could provide a better example.

Replace all occurences of `load_in_8bit` with bnb config

Update overview.md

* Fix has_file in offline mode

* harmonize env variable for offline mode

* Switch to HF_HUB_OFFLINE

* fix test

* revert test_offline to test TRANSFORMERS_OFFLINE

* Add new offline test

* merge conflicts

* docs

* Deprecate models
- graphormer
- time_series_transformer
- xlm_prophetnet
- qdqbert
- nat
- ernie_m
- tvlt
- nezha
- mega
- jukebox
- vit_hybrid
- x_clip
- deta
- speech_to_text_2
- efficientformer
- realm
- gptsan_japanese

* Fix up

* Fix speech2text2 imports

* Make sure message isn't indented

* Fix docstrings

* Correctly map for deprecated models from model_type

* Uncomment out

* Add back time series transformer and x-clip

* Import fix and fix-up

* Fix up with updated ruff

Update _redirects.yml

* add peft references

* add peft references

* Update docs/source/en/peft.md

* Update docs/source/en/peft.md

* Update docs

* Add PaliGemma resources

* Address comment

* Update docs

Update quicktour.md to fix broken link

Missing '/' in attention mask link in the transformers quicktour

* Fix link in dbrx.md

* remove "though this may not be up to date"

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

* chore: initial commit

* chore: adding imports and inits

* chore: adding the causal and classification code

* chore: adding names to the layers

* chore: using single self attn layer

* chore: built the model and layers

* chore: start with testing

* chore: docstring change, transpose fix

* fix: rotary embedding

* chore: adding cache implementation

* remove unused torch

* chore: fixing the indexing issue

* make fix-copies

* Use modeling_tf_utils.keras

* make fixup

* chore: fixing tests

* chore: adding past key value logic

* chore: adding multi label classfication test

* fix: switching on the built parameters in the layers

* fixing repo consistency

* ruff formats

* style changes

* fix: tf and pt equivalence

* removing returns from docstrings

* fix docstrings

* fix docstrings

* removing todos

* fix copies

* fix docstring

* fix docstring

* chore: using easier rotate_half

* adding integration tests

* chore: addressing review related to rotary embedding layer

* review changes

* [run-slow] mistral

* skip: test save load after resize token embedding

* style

---------
Co-authored-by: Matt <rocketknight1@gmail.com>

* Change in quantization docs

* Update overview.md

* Update docs/source/en/quantization/overview.md
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* refactor quant docs

* delete file

* rename to overview

* fix

* fix table

* fix

* add content

* fix library versions

* fix table

* fix table

* fix table

* fix table

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* replace to quantization_config

* fix aqlm snippet

* add DLAI courses

* fix

* fix table

* fix bulet points

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

* clean-up

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

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

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

* fixup

* Update tests/quantization/quanto_integration/test_quanto.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

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

* more suggestions

* mapping if torch available

* run tests & add 'support_quantized' flag

* fix jamba test

* revert, will be fixed by another PR

* codestyle

* HQQ and versatile cache classes

* final update

* typo

* make tests happy

---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update with new resizing and pad strategy

* Return pixel mask param

* Update inference in guide

* Fix empty compose

* Update guide

[doc] Add references to the fine-tuning blog and distil-whisper to Whisper doc.

* update video-llava

* Update docs/source/en/model_doc/video_llava.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* Update ignore index

* Update docs

* Update docs

* add V1 - adalomo not working yet

* add todo docs + refactor from comments

* adjust LR

* add docs

* add more elaborated test

* Apply suggestions from code review
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* fix

* push

* add accelerate check

* fix DDP case

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

* fix

* init kwargs

* safely add attribute

* revert to enum logic

* Update src/transformers/trainer.py

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

* add model_memory_anatomy to es/_toctree.yml

* copy model_memory_anatomy.md to es/

* translate first section

* translate doc

* chage forward activations

* fix sentence and and link to Trainer

* fix Trainer link

* first version

* fix sliding window

* fix style

* add sliding window cache

* fix style

* address comments

* fix test

* fix style

* move sliding window check inside cache init

* revert changes on irrelevant files & add comment on SlidingWindowCache

* address comments & fix style

fix style

* update causal mask

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] llama

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* revert CI from a10 to t4

* wrap up

* update docs with batch ex

* Update docs/source/en/model_doc/llava_next.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* accept nested list of img

---------
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add MistralForTokenClassification

* Add tests and docs

* Add token classification for Mixtral and Qwen2

* Save llma for token classification draft

* Add token classification support for Llama, Gemma, Persimmon, StableLm and StarCoder2

* Formatting

* Add token classification support for Qwen2Moe model

* Add dropout layer to each ForTokenClassification model

* Add copied from in tests

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Propagate suggested changes

* Style

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

* fix: missing dependencies

* fix: image classification dependencies

fix model id in docs

* Add resources

* Address comment

* Address comments

* Update docs/source/en/model_doc/idefics2.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update figure

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