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🌐 [i18n-KO] Translated vision-encoder-decoder.md to Korean#39563

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🌐 [i18n-KO] Translated vision-encoder-decoder.md to Korean#39563
jihyun-0611 wants to merge 6 commits into
huggingface:mainfrom
jihyun-0611:ko-vision-encoder-decoder.md

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@jihyun-0611

@jihyun-0611 jihyun-0611 commented Jul 21, 2025

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What does this PR do?

Translated the vision-encoder-decoder.md file of the documentation to Korean.
Thank you in advance for your review.

Part of #20179

Before reviewing

  • Check for missing / redundant translations (번역 누락/중복 검사)
  • Grammar Check (맞춤법 검사)
  • Review or Add new terms to glossary (용어 확인 및 추가)
  • Check Inline TOC (e.g. [[lowercased-header]])
  • Check live-preview for gotchas (live-preview로 정상작동 확인)

Who can review? (Initial)

May you please review this PR?
@4N3MONE, @yijun-lee, @jungnerd , @harheem

Before submitting

  • 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,
    Pull Request section?
  • Was this discussed/approved via a Github issue or the forum? 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, and
    here are tips on formatting docstrings.
  • Did you write any new necessary tests?

Who can review? (Final)

@stevhliu May you please review this PR?

@yijun-lee yijun-lee left a comment

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수고 많으셨습니다!

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@stevhliu stevhliu left a comment

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Nice thanks! We can merge once the feedback is addressed 🤗

@harheem harheem left a comment

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문서 번역하시느라 고생 많으셨고, 정말 감사합니다 🤗
아래쪽 auto doc에 대한 헤더에도 앵커를 달아줘야합니다! 반영해주시면 감사하겠습니다 :)
조금 더 잘 읽히는 문서가 되었으면 하여 몇 가지 표현을 수정하였습니다. 보시고 괜찮으시면 반영부탁드려요 ✨

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## 사전훈련된 인코더와 디코더에서 `VisionEncoderDecoderModel` 초기화[[initialising-visionencoderdecodermodel-from-a-pretrained-encoder-and-a-pretrained-decoder]]

[`VisionEncoderDecoderModel`]은 사전훈련된 인코더 체크포인트와 사전훈련된 디코더 체크포인트에서 초기화할 수 있습니다. 사전훈련된 Transformer 기반 비전 모델(*예:* [Swin](swin))은 인코더 역할을 할 수 있으며, 사전훈련된 오토인코딩 모델(*예:* BERT), 사전훈련된 인과적 언어 모델링(causal language modeling)(*예:* GPT2), 그리고 시퀀스-투-시퀀스 모델의 사전훈련된 디코더 부분(*예:* BART의 디코더)은 모두 디코더로 사용할 수 있습니다.

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Suggested change
[`VisionEncoderDecoderModel`]사전훈련된 인코더 체크포인트와 사전훈련된 디코더 체크포인트에서 초기화할 수 있습니다. 사전훈련된 Transformer 기반 비전 모델(*예:* [Swin](swin))은 인코더 역할을 할 수 있으며, 사전훈련된 오토인코딩 모델(*예:* BERT), 사전훈련된 인과적 언어 모델링(causal language modeling)(*예:* GPT2), 그리고 시퀀스-투-시퀀스 모델의 사전훈련된 디코더 부분(*예:* BART의 디코더)은 모두 디코더로 사용할 수 있습니다.
[`VisionEncoderDecoderModel`]사전 훈련된 인코더 체크포인트와 사전 훈련된 디코더 체크포인트에서 초기화할 수 있습니다. 사전 훈련된 Transformer 기반 비전 모델(*예:* [Swin](swin))은 인코더 역할을 할 수 있으며, 사전 훈련된 오토인코딩 모델(*예:* BERT), 사전 훈련된 인과적 언어 모델링(causal language modeling)(*예:* GPT2), 그리고 시퀀스-투-시퀀스 모델의 사전 훈련된 디코더 부분(*예:* BART의 디코더)은 모두 디코더로 사용할 수 있습니다.

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jihyun-0611 and others added 2 commits July 31, 2025 21:22
Co-authored-by: Yijun Lee <119404328+yijun-lee@users.noreply.github.com>
Co-authored-by: Harheem Kim <49297157+harheem@users.noreply.github.com>
Co-authored-by: Yijun Lee <119404328+yijun-lee@users.noreply.github.com>
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@jihyun-0611 jihyun-0611 marked this pull request as ready for review July 31, 2025 12:24
@stevhliu

stevhliu commented Aug 8, 2025

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Thanks, would you mind resolving the conflict?

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4 participants