🌐 [i18n-KO] Translated `compressed_tensor.md` to Korean by maximizemaxwell · Pull Request #39517 · huggingface/transformers

maximizemaxwell · 2025-07-19T07:20:47Z

What does this PR do?

Translated the compressed_tensor.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)

4N3MONE · 2025-07-19T07:39:14Z

번역 고생하셨습니다.

번역하신 내용을 읽으면서 23,25,96라인에 씌여 있는 '활성화' 라는 표현이 적절하게 글의 원래 의도를 나타내고 있지 못한 것 같아서 이 부분을 어떻게 하면 더 적절하게 표현할 수 있을 지 고민해보면 좋을 것 같아요!

인터넷을 찾아봐도 적절한 표현이 없는 것 같아서 우선 고민해본 몇 가지 번역 제안을 드립니다.

활성화 양자화 -> 활성화 함수 기반 양자화
활성화 정밀도 -> 활성화 함수 출력 정밀도

maximizemaxwell · 2025-07-20T04:14:16Z

제안해주신 단어를 반영하였고, line 96의 문장은 전반적으로 구조를 약간 바꾸었습니다,

Rocketknight1 · 2025-07-21T11:35:11Z

cc @stevhliu

harheem

은수님 좋은 번역 정말 감사합니다 ☺️
잘 읽히는 글이라 조금 욕심을 내서 수정 제안을 해보았습니다.

22~28 라인은 문장형인 것이 있고 단어로 끝나는 것이 있어서 단어로 끝나게 통일해보았습니다. 문장형으로 모두 통일하셔도 좋을 것 같아요! 편하게 의견주세요.

harheem · 2025-07-21T15:26:52Z

+
+[compressed-tensors](https://github.com/neuralmagic/compressed-tensors)는 [safetensors](https://github.com/huggingface/safetensors) 파일을 압축된 텐서 데이터 타입으로 확장해서, dense, int 양자화(int8), float 양자화(fp8), pack 양자화(int32로 패킹된 int4 또는 int8 가중치 양자화) 등 다양한 양자화·sparse 형식을 하나의 체크포인트 형식으로 저장하고 불러올 수 있게 합니다.
+
+compressed-tensors는 [PEFT](https://huggingface.co/docs/peft)를 사용한 파인튜닝을 지원하며, 다음과 같은 기능들을 제공합니다.


Suggested change

compressed-tensors는 [PEFT](https://huggingface.co/docs/peft)를 사용한 파인튜닝을 지원하며, 다음과 같은 기능들을 제공합니다.

compressed-tensors는 [PEFT](https://huggingface.co/docs/peft)를 사용한 미세 조정을 지원하며, 다음과 같은 기능들을 제공합니다.

glossary에 따라 '미세 조정'으로 수정하였습니다

harheem · 2025-07-21T15:32:04Z

+
+compressed-tensors는 [PEFT](https://huggingface.co/docs/peft)를 사용한 파인튜닝을 지원하며, 다음과 같은 기능들을 제공합니다.
+
+- fp8, int4, int8 가중치 및 활성화 함수 출력 정밀도.


Suggested change

- fp8, int4, int8 가중치 및 활성화 함수 출력 정밀도.

- fp8, int4, int8 가중치 및 활성화 함수 출력 정밀도

stevhliu

Thanks all, I'll merge once comments have been resolved! 🤗

Co-authored-by: Harheem Kim <49297157+harheem@users.noreply.github.com>

wo0jun

일부 리뷰해보았습니다. 참고 부탁드려요!

Co-authored-by: Woojun Jung <46880056+jungnerd@users.noreply.github.com>

4N3MONE

LGTM! 🤗

stevhliu · 2025-08-04T15:23:00Z

Thanks! Would you mind resolving the conflict before we merge please? 🤗

wo0jun · 2025-10-11T05:47:59Z

@maximizemaxwell 충돌만 해결하면 머지될 것 같습니닷! 확인 부탁드립니다!

ArthurZucker · 2026-10-20T13:25:18Z

Thanks for the PR, and sorry it didn't make it in! This branch is based on v4, and v5 is very different, so rather than rebasing we'd love to invite you to open a new PR against main using our latest tools and good practices:

Transformers tenets
mlinter and the modeling rules it enforces (make typing)
Modular transformers
Contributing guide

Closing this one in the meantime, thanks again!

maximizemaxwell added 4 commits July 19, 2025 15:34

feat: nmt draft

55df9d4

fix: improve translation accuracy and natural expressions

9ce0291

fix: applyed grammer check, improved naturaility

513e2e2

fix: update toctree.yml

457effe

maximizemaxwell added 2 commits July 20, 2025 13:10

fix: revised awkward words

42a8e44

fix: revised sentence in line96

eeb2258

harheem reviewed Jul 21, 2025

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stevhliu approved these changes Jul 21, 2025

View reviewed changes

maximizemaxwell and others added 4 commits July 22, 2025 01:20

Update compressed_tensors.md

c38688d

Co-authored-by: Harheem Kim <49297157+harheem@users.noreply.github.com>

Update compressed_tensors.md

1c98864

Co-authored-by: Harheem Kim <49297157+harheem@users.noreply.github.com>

Update compressed_tensors.md

8409f24

Co-authored-by: Harheem Kim <49297157+harheem@users.noreply.github.com>

Update compressed_tensors.md

5bea391

Co-authored-by: Harheem Kim <49297157+harheem@users.noreply.github.com>

maximizemaxwell marked this pull request as ready for review July 22, 2025 12:06

Merge branch 'main' into ko-compressed_tensor.md

c34cf28

wo0jun reviewed Jul 25, 2025

View reviewed changes

Comment thread docs/source/ko/quantization/compressed_tensors.md Resolved

Comment thread docs/source/ko/quantization/compressed_tensors.md Resolved

Comment thread docs/source/ko/quantization/compressed_tensors.md Resolved

maximizemaxwell and others added 3 commits July 31, 2025 21:45

compressed_tensors.md 업데이트

4037291

Co-authored-by: Woojun Jung <46880056+jungnerd@users.noreply.github.com>

compressed_tensors.md 업데이트

cf0a8da

Co-authored-by: Woojun Jung <46880056+jungnerd@users.noreply.github.com>

compressed_tensors.md 업데이트

6b4a97d

Co-authored-by: Woojun Jung <46880056+jungnerd@users.noreply.github.com>

4N3MONE approved these changes Aug 3, 2025

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maximizemaxwell added 2 commits August 5, 2025 13:10

fix: toctree from main

dd73f91

fix: update toctree

5d3a712

evalstate mentioned this pull request Apr 29, 2026

Cumulative feature and defect updates from recent Transformers PRs evalstate/transformers#42

Open

ArthurZucker closed this Oct 20, 2026


		[compressed-tensors](https://github.com/neuralmagic/compressed-tensors)는 [safetensors](https://github.com/huggingface/safetensors) 파일을 압축된 텐서 데이터 타입으로 확장해서, dense, int 양자화(int8), float 양자화(fp8), pack 양자화(int32로 패킹된 int4 또는 int8 가중치 양자화) 등 다양한 양자화·sparse 형식을 하나의 체크포인트 형식으로 저장하고 불러올 수 있게 합니다.

		compressed-tensors는 [PEFT](https://huggingface.co/docs/peft)를 사용한 파인튜닝을 지원하며, 다음과 같은 기능들을 제공합니다.


		compressed-tensors는 [PEFT](https://huggingface.co/docs/peft)를 사용한 파인튜닝을 지원하며, 다음과 같은 기능들을 제공합니다.

		- fp8, int4, int8 가중치 및 활성화 함수 출력 정밀도.

	- fp8, int4, int8 가중치 및 활성화 함수 출력 정밀도.
	- fp8, int4, int8 가중치 및 활성화 함수 출력 정밀도

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