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There is typo in the original hyperlink.

Below is the original version:
Based on the script [`run_translation_no_trainer.py`](https://github.com/huggingface/transformers/blob/main/examples/pytorch/translation/**run_translationn_no_trainer.py**).

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

* merge conflicts

* bos and eos in datacollator

* (temp) hardcode removal of attention mask

* freeze encoder

* actually freeze encoder

* set max length / num beams according to gen kwargs

* (temp) fix tests

* don't pop attn mask

* override return attention mask config from Hub

* Hub configs updated 🤗

* final fixes

* update type annotations

* backward comp

Part of #20183
docs: add relevant labels to i18n issue template
fix: typo on completion count

docs: i18n: first draft of index page
docs: fix: first revision of index page
docs: i18n: missed section - supported frameworks
docs: fix: second revision of index page
review by @ArthurZucker

refactor: remove untranslated files from korean
docs: fix: remove untranslated references from toctree.yml
feat: enable korean docs in gh actions
docs: feat: add in_translation page as placeholder
docs: bug: testing if internal toc need alphabet chars
docs: fix: custom english anchor for non-alphanumeric headings
review by @sgugger

docs: i18n: translate comments on install methods in _config.py
docs: refactor: more concise wording for translations

* fix slow test

* Update tests/models/roc_bert/test_modeling_roc_bert.py

* initial commit

* Update modeling_whisper.py

* Fixing Tests

* modeling_vision_text_dual_encoder

* modeling_vision_encoder_decoder

* Update modeling_vit.py

* Update modeling_vit_msn.py

* Update modeling_trajectory_transformer.py

* style

* Update modeling_time_series_transformer.py

* Update modeling_time_series_transformer.py

* Update modeling_segformer.py

* Update modeling_plbart.py

* Update modeling_dpt.py

* Update modeling_deit.py

* Update modeling_dpt.py

* Update modeling_esm.py

* Update modeling_fnet.py

* Update modeling_fnet.py

* Update modeling_fnet.py

* Update modeling_flava.py

* Update modeling_flava.py

* Update modeling_layoutlmv3.py

* Update modeling_levit.py

Proposal Remove the weird `inspect` in ASR pipeline and make WhisperEncoder just nice to use. (#19571)

* Proposal Remove the weird `inspect` in ASR pipeline and make
WhisperEncoder just nice to use.

It seems that accepting `attention_mask` is kind of an invariant of our
models. For Seq2Seq ASR models, we had a special comment on how it
actually was important to send it.

`inspecting` seems pretty brittle way to handle this case.
My suggestion is to simply add it as an kwarg that and just ignoring
it with the docstring explaining why it's ignored.

* Fixup.

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

* Doc fixing .
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

Fixed a grammatical error.

* First draft

* Remove scatter dependency

* Add require_torch

* update vectorized sum test, add clone call

* remove artifacts

* fix style

* fix style v2

* remove "scatter" mentions from the code base

* fix isort error
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* add model files etc for MobileNetV2

* rename files for MobileNetV1

* initial implementation of MobileNetV1

* fix conversion script

* cleanup

* write docs

* tweaks

* fix conversion script

* extract hidden states

* fix test cases

* make fixup

* fixup it all

* rename V1 to V2

* fix checkpoints

* fixup

* implement first block + weight conversion

* add remaining layers

* add output stride and dilation

* fixup

* add tests

* add deeplabv3+ head

* a bit of fixup

* finish deeplab conversion

* add link to doc

* fix issue with JIT trace

in_height and in_width would be Tensor objects during JIT trace, which caused Core ML conversion to fail on the remainder op. By making them ints, the result of the padding calculation becomes a constant value.

* cleanup

* fix order of models

* fix rebase error

* remove main from doc link

* add image processor

* remove old feature extractor

* fix converter + other issues

* fixup

* fix unit test

* add to onnx tests (but these appear broken now)

* add post_process_semantic_segmentation

* use google org

* remove unused imports

* move args

* replace weird assert

* Apply fix

* Fix test

* Remove another argument which is not used

* Fix pipeline test

* Add argument back, add deprecation warning

* Add warning add other location

* Use warnings instead

* Add num_channels to config
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

* [processor] Add 'model input names' property

* add test

* no f string

* add generic property method to mixin

* copy to multimodal

* copy to vision

* tests for all audio

* remove ad-hoc tests

* style

* fix flava test

* fix test

* fix processor code

* Fix arg names for our models

* Clean out the other uses of "residx" in infer()

* make fixup

* Check ImageProcessingMixin in OnnxConfig.generate_dummy_inputs

* Check ImageProcessingMixin in OnnxConfig.generate_dummy_inputs

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

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

* Adding support for LayoutLMvX variants for `object-detection`.

* Revert bogs `layoutlm` feature extractor which does not exist (it was a
V2 model) .

* Updated condition.

* Handling the comments.

* Add RoCBertTokenizer to TOKENIZER_MAPPING_NAMES

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

* Add resource

* Add tag
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* TrOCR processor uses an image processor

* Update VisionEncoderDecoder

* Add feature_extractor_class property

* move generation_*.py src files into generation/*.py

* populate generation.__init__ with lazy loading

* move imports and references from generation.xxx.object to generation.object

* Attempting to test automatically the `_keys_to_ignore`.

* Style.

* First fix pass.

* Moving test on its own.

* Another batch.

* Second round removing BatchNorm

* Fixing layoutlmv{2,3} + support older Python.

* Disable miss missing warning.

* Removing dodgy additions.

* Big pass.

* mbart.

* More corrections.

* Fixup.

* Updating test_correct_missing_keys

* Add escape hatch for when the head has no extra params so doesn't need

the missing keys check.

* Fixing test.

* Greener.

* Green ! (except for weird splinter bug).

* Adding a test about `named_parameters` usage.

* Shorten message.

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* After rebase modifications.

* More explicit condition checking.

* Fixing slow tests issues.

* Remove extra pdb.

* Remove print.

* Attempt to make failure consistent + fixing roc_bert.

* Removing the seed  (all tests passing with it).
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update doctest values

* Update copy statement

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

* Remove BertConfig inheritance from RobertaConfig

* Fix Typo: BERT to RoBERTa

* Improve tiny model creation script

* sort the list of models to upload
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* AutoImageProcessor skeleton

* Update references

* Add mapping in init

* Add model image processors to __init__ for importing

* Add AutoImageProcessor tests

* Fix up

* Image Processor documentation

* Remove pdb

* Update docs/source/en/model_doc/mobilevit.mdx

* Update docs

* Don't add whitespace on json files

* Remove fixtures

* Move checking model config down

* Fix up

* Add check for image processor

* Remove FeatureExtractorMixin in docstrings

* Rename model_tmpfile to config_tmpfile

* Don't make None if not in image processor map

* Make default labels for non-pretrained models

* Fix the has_labels test instead