noamaanMulla-03/transformers-issues huggingface dataset:
🌐 [i18n-KO] Translated `image_feature_extraction.md` to Korean
Author: mreraser
Pull request: yes

<!-- PR의 제목은 "🌐 [i18n-KO] Translated `<your_file>.md` to Korean" 으로 부탁드립니다 -->
# What does this PR do?

Translated the `image_feature_extraction.md` file of the documentation to Korean.
Thank you in advance for your review. 

Part of https://github.com/huggingface/transformers/issues/20179

## Before reviewing
- [x] Check for missing / redundant translations (번역 누락/중복 검사)
- [x] Grammar Check (맞춤법 검사)
- [x] Review or Add new terms to glossary (용어 확인 및 추가)
- [x] Check Inline TOC (e.g. `[[lowercased-header]]`)
- [x] Check live-preview for gotchas (live-preview로 정상작동 확인)

## Who can review? (Initial)

<!-- 1. 위 체크가 모두 완료된 뒤에만 N조 팀원들에게 리뷰 요청하는 아래 주석을 노출해주세요! 차례대로 1 ~ 5조 -->
May you please review this PR?
@jun048098, @yijun-lee, @mreraser, @shinhyunji36, @heuristicwave
<!-- @win2dvp21, @enchantee00, @fabxoe, @1kmmk1, @junejae -->
<!-- @SeungAhSon, @Jwaminju, @thsamajiki, @4N3MONE, @jungnerd -->
<!-- @mjk0618, @cjfghk5697, @ahnjj, @JinukHong, @nuatmochoi -->
<!-- @010kim, @chhaewxn, @boyunJang, @jeongiin, @harheem -->

## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [x] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?

## Who can review? (Final)

<!-- 2. N조 팀원들과 리뷰가 끝난 후에 아래 주석을 노출해주세요! -->
Hello @stevhliu !  May you please review this PR? Thank you! 

Have a nice day :)

Comments:
> @mreraser 가장 빠르게 문서를 잘 번역해주셔서 감사합니다!

소중한 리뷰 감사합니다 😄 @heuristicwave 

고심해서 번역하신 것이 느껴지네요! 많이 배웠습니다. :) 번역하느라 고생 많으셨습니다 😃 @mreraser 

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32239). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
Fix references to model google mt5 small
Author: JuanFKurucz
Pull request: yes

# What does this PR do?

Fixes the reference to the model `mt5-small` that currently seems to be hosted under the account `google` and not `google-mt5` https://huggingface.co/google/mt5-small


## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->

Documentation: @stevhliu

Comments:
UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
Author: g-jing
Pull request: no
Labels: name: wontfix

When I finetune Bert with simple_lm_finetuning.py, there seems an error:
     "UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector."

Will it influence the performance of the finetuning process ? Thanks in advance for any suggestion.

Comments:
It should be fine. There are probably your output losses.

@thomwolf  Thanks for your reply. Could you explain more about why this happens ? I am still confused though

Maybe it is caused by calculating the loss in the model's forward function.


This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.


I have the same problem in version 2.2.1, what can it be?

In my case, it doesn’t influence the results

On Mon, Jan 6, 2020 at 5:19 AM calusbr <notifications@github.com> wrote:

> I have the same problem in version 2.2.1, what can it be?
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/transformers/issues/852?email_source=notifications&email_token=AKRMVV4J4UT6HCXEEMOYBGDQ4MVV3A5CNFSM4IFUKP3KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEIFNJAI#issuecomment-571135105>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/AKRMVV37AGO5AXJNPSGUVLTQ4MVV3ANCNFSM4IFUKP3A>
> .
>


In my case, the speed of training with 4 GPU is the same as 1 GPU. How solve the speed issues?

👀

> In my case, the speed of training with 4 GPU is the same as 1 GPU. How solve the speed issues?

@sociengineer , sorry for bothering you, may I ask if you have solved this problem as I meet the same one. Thanks!

> > In my case, the speed of training with 4 GPU is the same as 1 GPU. How solve the speed issues?
> 
> @sociengineer , sorry for bothering you, may I ask if you have solved this problem as I meet the same one. Thanks!

@XLechter I couldn't resolve the problem 😭

This warning is still there and it's a bummer
Docs: Fixed WhisperModel.forward’s docstring link
Author: Sai-Suraj-27
Pull request: yes

# What does this PR do?
I changed the link to a permalink, because the file is being modified frequently.

Fixes # (issue)


## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?
Documentation: @stevhliu

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32498). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
EncoderDecoderModel works poorly with Mlflow
Author: alexyalunin
Pull request: no
Labels: name: wontfix

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 4.0.0

## Description
Mlflow keeps track of model config parameters, EncoderDecoderConfig has `encoder` and `decoder` parameters which are basically configs of encoder and decoder. They are converted first `to_dict` and then to string `str()` by mlflow resulting in a long string that can not be fit. The `MAX_PARAM_VAL_LENGTH` of Mlflow is set to 250 and AFAIK can not be changed. 

This result in an error:
`MlflowException: Param value '{'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'use_bfloat16': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'is_encoder_decoder': False, 'is_decoder': False, 'add_cross_attention': Fa' had length 1669, which exceeded length limit of 250`

My solution for training phase is:
```
class DummyClass:
    def to_dict(self):
        return {}
    
model.config.encoder = DummyClass()
model.config.decoder = DummyClass() 
```
@patrickvonplaten

Comments:
Thanks for your proposed solution @alexyalunin ! 

I don't really think that this is a problem on our side. I think MLFlow should better handle this no? 

Probably, but since you use mlflow inside your library people might expect it working with your models. I won't open the issue in mlflow repo, I leave it to someone who encounters this error again. @patrickvonplaten You can close this issue then. 

This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.

If you think this still needs to be addressed please comment on this thread.

I'm having the same problem finetuning on a T5 model.  I attempted @alexyalunin 's solution of creating a DummyClass above but it didn't change the error.
Fix link to autoclass_tutorial.md in i18n.md
Author: JuanFKurucz
Pull request: yes

# What does this PR do?

Fixes broken link that loads a 404 not found page.

## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->

Documentation: @stevhliu

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32501). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
Fix typo: depracted -> deprecated
Author: tomaarsen
Pull request: yes

Hello!

## Pull Request overview
* Fix typo

## Details
This should speak for itself.

cc @itazap @ArthurZucker 

- Tom Aarsen

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32489). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
One character error
Author: avdvg
Pull request: no
Labels: name: bug

### System Info

Hello, I was reading the tutorial https://huggingface.co/docs/transformers/v4.41.3/zh/llm_tutorial and I found that there was an error with one character.




### Who can help?

_No response_

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

this error in  https://huggingface.co/docs/transformers/v4.41.3/zh/llm_tutorial.
![image](https://github.com/user-attachments/assets/80ef33f2-03cf-48de-a59c-837649dc9ddf)

### Expected behavior

please change "_通过迭代调用模型及其自身的生成输出来生成文本的推理过程，。_" to "_通过迭代调用模型及其自身的生成输出来生成文本的推理过程。_"


Comments:
Implement `generate` (inference) for torch exported text-generation models
Author: guangy10
Pull request: no
Labels: name: Feature request

name: Generation

name: ExecuTorch

### Feature request

Unlike `torch.compile`, `torch.export` only export the inner transformer to predict a single token for text-generation models. The autoregressive logics are not included in the exported artifact. For ExecuTorch Runtime, the autoregressive logics is implemented there, either directly in c++ ([code pointer](https://github.com/pytorch/executorch/blob/main/examples/models/llama2/runner/runner.cpp#L310-L415)) or python ([code pointer](https://github.com/pytorch/executorch/blob/main/examples/models/llama2/runner/generation.py#L70-L124)). Here is a minimal `generate` impl in a test for Phi3-mini in 🤗  ([code pointer](https://github.com/huggingface/transformers/blob/543df489147412efb20575c3c2a3fb69a18ac107/tests/models/phi3/test_modeling_phi3.py#L73)). 

Instead of duplicate the generate logics for each exported model, it's better to have a common implementation of `generate` that can be used by any exported text-generation mdoel.

### Motivation

To support the new "Export to ExecuTorch" workflow. This would enable users to have a unified `generate` experience as they run inference using eager or compiled model. 

### Your contribution

TBD

Comments:
TrOCR is ExecuTorch compatible
Author: guangy10
Pull request: no
Labels: name: Feature request

name: ExecuTorch

### Feature request

Enable TrOCR to ["Export to ExecuTorch"](https://github.com/huggingface/transformers/issues/32253) workflow

### Motivation

See details in #32253

### Your contribution

TBD

Comments:
Bart/Wav2Vec2 is ExecuTorch compatible
Author: guangy10
Pull request: no
Labels: name: Feature request

name: ExecuTorch

### Feature request

Enable Bart/Wav2Vec2 to ["Export to ExecuTorch"](https://github.com/huggingface/transformers/issues/32253) workflow

### Motivation

See details in #32253

### Your contribution

TBD

Comments:
Fix add-new-model-like
Author: molbap
Pull request: yes

Better version of #31753 that was actually due to the `image_processor_class` attribute being now a tuple with (slow, fast). All the addition logic relies on having one class only there, so we return only the first element.


Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_31773). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Test errors are hub read timeouts. 

cc @molbap we'll need a rebase here before anything! 

Forgot to merge this - @ArthurZucker should be good to go
Test Results for sync branch upstream_sync
Author: Cemberk
Pull request: no

### Unit Test Results\n```\n\n```\n\n### Performance Test Results\n```\n\n```

Comments:
Hi @Cemberk, 

What is the issue you're experiencing? 


@amyeroberts sorry, no issue, working on an automation feature 

@Cemberk Please refrain from using our repo for your sandbox
Fix chinese clip
Author: molbap
Pull request: yes

# What does this PR do?

Fixes #32280 , weight loading issue

cc @qubvel @amyeroberts, linked issue shows a weight loading error when loading the text part of `ChineseCLIP`. It's an edge case due to checkpoint structure + the way ChineseCLIPModel is created. This separates ChineseCLIPModel parts a bit better, while hopefully not breaking anything. 
To clarify: it will not break preexisting checkpoints of ChineseCLIPModel BUT it _will_ break ckpts of `ChineseCLIPTextModel` if such exist. 



Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32291). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Should be good to go  @amyeroberts @qubvel !
🌐 [i18n-KO] Translated `eetq.md` to Korean
Author: jun048098
Pull request: yes

<!-- PR의 제목은 "🌐 [i18n-KO] Translated `eetq.md` to Korean" 으로 부탁드립니다 -->
# What does this PR do?

Translated the `eetq.md` file of the documentation to Korean.
Thank you in advance for your review. 

Part of https://github.com/huggingface/transformers/issues/20179

## Before reviewing
- [x] Check for missing / redundant translations (번역 누락/중복 검사)
- [x] Grammar Check (맞춤법 검사)
- [x] Review or Add new terms to glossary (용어 확인 및 추가)
- [x] Check Inline TOC (e.g. `[[lowercased-header]]`)
- [ ] Check live-preview for gotchas (live-preview로 정상작동 확인)

## Who can review? (Initial)

<!-- 1. 위 체크가 모두 완료된 뒤에만 N조 팀원들에게 리뷰 요청하는 아래 주석을 노출해주세요! 차례대로 1 ~ 5조 -->
<!-- May you please review this PR? -->
@jun048098, @yijun-lee, @mreraser, @shinhyunji36, @heuristicwave
<!-- @win2dvp21, @enchantee00, @fabxoe, @1kmmk1, @junejae -->
<!-- @SeungAhSon, @Jwaminju, @thsamajiki, @4N3MONE, @jungnerd -->
<!-- @mjk0618, @cjfghk5697, @ahnjj, @JinukHong, @nuatmochoi -->
<!-- @010kim, @chhaewxn, @boyunJang, @jeongiin, @harheem -->

## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [x] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?

## Who can review? (Final)

<!-- 2. N조 팀원들과 리뷰가 끝난 후에 아래 주석을 노출해주세요! -->
@stevhliu May you please review this PR?

Comments:
@jun048098 Before reviewing 체크리스트도 체크 부탁드려요~

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32352). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
🌐 [i18n-KO] Translated `fsdp.md` to Korean
Author: win2dvp21
Pull request: yes

<!-- PR의 제목은 "🌐 [i18n-KO] Translated `<your_file>.md` to Korean" 으로 부탁드립니다 -->
# What does this PR do?

Translated the `fsdp.md` file of the documentation to Korean.
Thank you in advance for your review. 

Part of https://github.com/huggingface/transformers/issues/20179

## Before reviewing
- [x] Check for missing / redundant translations (번역 누락/중복 검사)
- [x] Grammar Check (맞춤법 검사)
- [x] Review or Add new terms to glossary (용어 확인 및 추가)
- [x] Check Inline TOC (e.g. `[[lowercased-header]]`)
- [ ] Check live-preview for gotchas (live-preview로 정상작동 확인)

## Who can review? (Initial)

<!-- 1. 위 체크가 모두 완료된 뒤에만 N조 팀원들에게 리뷰 요청하는 아래 주석을 노출해주세요! 차례대로 1 ~ 5조 -->
May you please review this PR?
<!-- @jun048098, @yijun-lee, @mreraser, @shinhyunji36, @heuristicwave -->
@win2dvp21, @enchantee00, @fabxoe, @1kmmk1, @junejae
<!-- @SeungAhSon, @Jwaminju, @thsamajiki, @4N3MONE, @jungnerd -->
<!-- @mjk0618, @cjfghk5697, @ahnjj, @JinukHong, @nuatmochoi -->
<!-- @010kim, @chhaewxn, @boyunJang, @jeongiin, @harheem -->

## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [x] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?

## Who can review? (Final)

<!-- 2. N조 팀원들과 리뷰가 끝난 후에 아래 주석을 노출해주세요! -->
@stevhliu May you please review this PR?

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32261). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.