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* control first downsample stride

* reduce first only works for ResNetBottleNeckLayer

* fix param name

* fix style

fix docstrings for vanilla clip

* Fix stale bot

* Comments

* removed donutimageprocessor from objects_to_ignore

* added docstring for donutimageprocessor

* readding donut file

* moved docstring to correct location

fix docstring for CLIPImageProcessor

* fix docstrings for CLIP configs

* black formatted

* fix typos in idefics.md

Two typos found in reviewing this documentation.

1) max_new_tokens=4, is not sufficient to generate "Vegetables" as indicated - you will get only "Veget". (incidentally - some mention of how to select this value might be useful as it seems to change in each example)

2) inputs = processor(prompts, return_tensors="pt").to(device) as inputs need to be on the same device (as they are in all other examples on the page)

* Update idefics.md

Change device to cuda explicitly to match other examples

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

* fix OpenAI GPT, GPT-2 links

* fix Llama2 link

Update test_integration.py

Fixed malapropism clone>copy

* Convert checkpoints

* Update doc test

* Address comment

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

* make sure eos and bos are properly handled for fast tokenizer

* fix code llama as well

* nits

* fix the conversion script as well

* fix failing test

* remove SharedDDP as it was drepracated

* apply review suggestion

* make style

* Oops,forgot to remove the compute_loss context manager in Seq2SeqTrainer.

* remove the unnecessary conditional statement

* keep the logic of IPEX

* clean code

* mix precision setup & make fixup

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Co-authored-by: statelesshz <jihuazhong1@huawei.com>

* fix

* fix

* Fix

* Fix

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

* remove unnecessary unsqueeze-squeeze in llama

* correct other models

* fix

* revert gpt_neox_japanese

* fix copie

* fix test

* Update tokenization_code_llama_fast.py

* Update test_tokenization_code_llama.py

* Update test_tokenization_code_llama.py

* Remove unnecessary `view` of `position_ids` in `modeling_llama`

When `position_ids` is `None`, its value is generated using
`torch.arange`, which creates a tensor of size `(seq_length +
past_key_values_length) - past_key_values_length = seq_length`. The
tensor is then unsqueezed, resulting in a tensor of shape `(1,
seq_length)`. This means that the last `view` to a tensor of shape
`(-1, seq_length)` is a no-op.

This commit removes the unnecessary view.

* Remove no-op `view` of `position_ids` in rest of transformer models

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

* build the table in index.md with links to the model_doc

* removed list generation on index.md

* fixed missing models

* make style

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

don't close clearml task if it was created externally

* feat: close #26566, changed model & config files to accept arbitary in and out channels

* updated docstrings

* fix: linter error

* fix: update Copy docstrings

* fix: linter update

* fix: rename num_channels_in to num_channels to prevent breaking changes

* fix: make num_channels_out None per default

* Update src/transformers/models/swin2sr/configuration_swin2sr.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix: update tests to include num_channels_out

* fix:linter

* fix: remove normalization with precomputed rgb values when #input_channels!=#output_channels

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Co-authored-by: marvingabler <marvingabler@outlook.de>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix silent bug `keep_in_fp32` modules

* final fix

* added a common test.

* Trigger CI

* revert

* Make `ModelOutput` serializable

Original PR from diffusers : https://github.com/huggingface/diffusers/pull/5234

* Black

* fix

* fix

* fix

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

* Set `presents=None` when `use_cache` is set to False for activation ckpt

* Update modeling_falcon.py

* fix black

* Faster rotary embedding for GPTNeoX

* there might be un-necessary moves from device

* fixup

* fix dtype issue

* add copied from statements

* fox copies

* oupsy

* add copied from Llama for scaled ones as well

* fixup

* fix

* fix copies

fix

* translate installation to zh

* fix translation typo

* fix wav2vec2 doctest

* suggestion

* fix

* final fix

* revert since we need AddedTokens

skip flaky

Fix bug in convert_t5x_checkpoint_to_pytorch.py