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Revert "Use `dash==2.8.1` for now for daily CI (#22227)"

This reverts commit 53218671.

* Add kernel size to NATTEN's QK arguments.

The new NATTEN 0.14.5 supports PyTorch 2.0, but also adds an additional
argument to the QK operation to allow optional RPBs.

This ends up failing NATTEN tests.

This commit adds NATTEN back to circleci and adds the arguments to get
it working again.

* Force NATTEN >= 0.14.5

fix(docs): task guide links in model docs

removed .mdx extension

* Add LlamaForSequenceClassification

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

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

* Add docstring

* Add test

* Add input embedding getter and setter

* Remove dead code

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

* fix AutoTP in deepspeed could not work for bloom
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* add a method in BloomModel to build ailib
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* LLaMA house-keeping

* Doc links

* added doc to toc, auto tip with  supported models, mention of task guide in model docs

* make style

* removed "see also"

* minor fix

Use dash 2.8.1 for now
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Co-authored-by: yue kun <yuekun.wp@alibaba-inc.com>

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

* py38 + torch 2

* increment cache versions

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

* fixes a typo

* .

* add `accelerate` support for XGLM

* fix order

* Temporarily fix https://github.com/microsoft/onnx-converters-private/issues/143

* Reduced column width

* Fix formatting.

* Revert "Temporarily fix https://github.com/microsoft/onnx-converters-private/issues/143"

This reverts commit 6e95a108042118d204da447729f3834affa354fc.

* Fix export error.

* Revert "Fix formatting."

This reverts commit 8310f60da10358edbdf77a2a2f3c83ee55066cb8.

* Propagated changes made in SwinV2 to Swin2SR

* Update UNCONVERTIBLE_MODEL_ARCHITECTURES

* Deal with 2 model tester classes in single test file

* Deal with 2 model tester classes in single test file

* Deal with 2 model tester classes in single test file

* make style and quality

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

* LLaMA

* sharding and docs

* tweak

* black

* inits

* ruff

* LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP

* init

* no checkpoint

* docs

* ruff

* type_vocab_size

* tokenizer fixes

* tokenizer fixes

* Update tokenization_llama.py

* Update tokenization_llama.py

* Update configuration_llama.py

* Update modeling_llama.py

* tokenizer add_bos by default

* licenses

* remove decoder

* norms and mlp

* rope overhaul

* tweaks

* black

* mention OPT implementation

* off-by-one naming

* typo

* fix

* tokenization fix and slicing bug

* padding config

* cleanup

* black

* update tests

* undo typo

* fix vocab caching logic

* ruff

* docbuilder

* attn fix from BlackSamorez

* initial feedback

* typo

* docs

* llama case

* llama case

* load checkpoint docs

* comment about tokenizer

* tokenizer defaults

* clear past_key_values if use_cache=False

* last tweaks

* last tweaks

* last tweaks

* last tweaks

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Co-authored-by: Stella Biderman <stellabiderman@gmail.com>

* LLaMA

* sharding and docs

* tweak

* black

* inits

* ruff

* LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP

* init

* no checkpoint

* docs

* ruff

* type_vocab_size

* tokenizer fixes

* tokenizer fixes

* Update tokenization_llama.py

* Update tokenization_llama.py

* Update configuration_llama.py

* Update modeling_llama.py

* tokenizer add_bos by default

* licenses

* remove decoder

* norms and mlp

* rope overhaul

* tweaks

* black

* mention OPT implementation

* off-by-one naming

* typo

* fix

* tokenization fix and slicing bug

* padding config

* cleanup

* black

* update tests

* undo typo

* fix vocab caching logic

* ruff

* docbuilder

* attn fix from BlackSamorez

* initial feedback

* typo

* docs

* llama case

* llama case

* load checkpoint docs

* comment about tokenizer

* tokenizer defaults

* clear past_key_values if use_cache=False

* last tweaks

* last tweaks

* last tweaks

* last tweaks

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Co-authored-by: Stella Biderman <stellabiderman@gmail.com>

* Tranlstion Italian: migration

* Update migration.mdx

minor fixes

* Update _toctree.yml

* Delete migration.mdx

* Add italian translation of migration.mdx

* Update of migration.mdx translation and toctree

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

Fix align docs typo

* Deal with torch-tensorrt

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

* t5 remove data dependency

* make style

* make fix-copies

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Co-authored-by: Prathik Rao <prathikrao@microsoft.com>

* Use return_loss for BridgeTowerForContrastiveLearning, add example

* fix tests

* Update example in BridgeTowerForContrastiveLearning

* Update test_modeling_bridgetower.py

* update model output format

* minor update

* Update src/transformers/models/bridgetower/modeling_bridgetower.py

* make style

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Co-authored-by: Tiep Le <97980157+tileintel@users.noreply.github.com>
Co-authored-by: Tiep Le <tiep.le@intel.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix regression in pipeline when device=-1 is passed

* Add regression test

Revert changes

Fix: unfinished_sequences with correct device 

The original code was causing errors when running torch.jit.trace due to the tensor options being incorrect. I fixed this by using torch.ones to create a tensor with the correct device and dtype. This should resolve the issue with running torch.jit.trace.

Revert "Enforce same behavior as PyTorch 2.0 for older versions (#22136)"

This reverts commit 1c801d65.

* [trainer] add --optim adamw_torch_fused

* change optim default

* deal with non-torch

* revert default change; prep; add fp16/amp assert

* typo

* typo

* Don't rescale if in and in range 0-255

* Raise value error if int values too large

* Update tests/test_image_transforms.py

* Update tests/test_image_transforms.py

* create MaskedImageCompletionOutput

* fix bugs

* fix bugs

* Fix big model inference for T5 models in float16

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Style

* Trigger CI with latest release

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

* added translated files

added perf_train_cpu and perf_train_cpu_many

* updated toctree

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

* Add ConvNeXt V2 to transformers
* TF model is separated from the PR to fix issues