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🌐 [i18n-KO] Translated eetq.md to Korean #32352

Merged
merged 9 commits into from
Aug 8, 2024
Merged

🌐 [i18n-KO] Translated eetq.md to Korean #32352

merged 9 commits into from
Aug 8, 2024

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jun048098
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@jun048098 jun048098 commented Jul 31, 2024 •
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What does this PR do?

Translated the eetq.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)

@jun048098, @yijun-lee, @mreraser, @shinhyunji36, @heuristicwave

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,
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  • Was this discussed/approved via a Github issue or the forum? Please add a link
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  • 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?

@jun048098 jun048098 marked this pull request as ready for review July 31, 2024 15:56
junejae
junejae suggested changes Aug 3, 2024
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@jun048098
아직 OSSCA 팀원들에게 리뷰/검토되지 않은 PR입니다. PR의 상태를 Draft로 변경 부탁드립니다.

This PR has never been reviewed by OSSCA members, Please change your PR's status to Draft.

@jun048098 jun048098 marked this pull request as draft August 3, 2024 16:26
heuristicwave
heuristicwave reviewed Aug 4, 2024
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docs/source/ko/quantization/eetq.md Outdated

# EETQ [[eetq]]

[EETQ](https://github.com/NetEase-FuXi/EETQ) 라이브러리는 NVIDIA GPU에 대해 int8 채널별(per-channel) weight-only quantization을 지원합니다. 고성능 GEMM 및 GEMV 커널은 FasterTransformer 및 TensorRT-LLM에서 가져왔습니다. 캘리브레이션 데이터셋이 필요 없으며, 모델을 사전에 양자화할 필요도 없습니다. 또한, 채널별 양자화(per-channel quantization) 덕분에 정확도 저하가 미미합니다.
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Suggested change
[EETQ](https://github.com/NetEase-FuXi/EETQ) 라이브러리는 NVIDIA GPU에 대해 int8 채널별(per-channel) weight-only quantization을 지원합니다. 고성능 GEMM 및 GEMV 커널은 FasterTransformer 및 TensorRT-LLM에서 가져왔습니다. 캘리브레이션 데이터셋이 필요 없으며, 모델을 사전에 양자화할 필요도 없습니다. 또한, 채널별 양자화(per-channel quantization) 덕분에 정확도 저하가 미미합니다.
[EETQ](https://github.com/NetEase-FuXi/EETQ) 라이브러리는 NVIDIA GPU에 대해 int8 채널별(per-channel) 가중치 전용 양자화(weight-only quantization)를 지원합니다.
고성능 GEMM 및 GEMV 커널은 FasterTransformer 및 TensorRT-LLM에서 가져왔습니다. 보정(calibration) 데이터셋이 필요 없으며, 모델을 사전에 양자화할 필요도 없습니다. 또한, 채널별 양자화(per-channel quantization) 덕분에 정확도 저하가 미미합니다.

개행과 calibration datasets에 대한 의견을 남겨두었습니다.

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@jun048098 jun048098 Aug 6, 2024 •
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weight-only quantization 은 intel에서 제공하는 extension이라 번역이 적절한지 고민하고 있었습니다
#링크

추가로 검색 결과 calibration은 교정으로 사용하는 듯합니다. 교정으로 개행하겠습니다
#링크

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@jun048098 Before reviewing 체크리스트도 체크 부탁드려요~

shinhyunji36
shinhyunji36 reviewed Aug 6, 2024
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다른 분들이 리뷰해주신 부분 외에 특별한 리뷰 사항을 발견하지 못했습니다! 고생 하셨습니다 😃

@jun048098 @mreraser
fix: resolve suggestions
a3332eb 
Co-authored-by: Jiwook Han <33192762+mreraser@users.noreply.github.com>
yijun-lee
yijun-lee suggested changes Aug 6, 2024
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개행 이외에는 딱히 수정할 곳이 없어보입니다! 수고하셨습니다.

docs/source/ko/quantization/eetq.md Outdated Show resolved Hide resolved
docs/source/ko/quantization/eetq.md Outdated
```

또는 소스 코드 https://github.com/NetEase-FuXi/EETQ 에서 설치할 수 있습니다. EETQ는 CUDA 기능이 8.9 이하이고 7.0 이상이어야 합니다.

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22, 26, 28, 37번 라인에 원문과 다른 개행이 있는 것 같습니다.

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jun048098
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개행 제거

docs/source/ko/quantization/eetq.md Outdated Show resolved Hide resolved
docs/source/ko/quantization/eetq.md Outdated Show resolved Hide resolved
docs/source/ko/quantization/eetq.md Outdated Show resolved Hide resolved
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@jun048098 jun048098 marked this pull request as ready for review August 6, 2024 12:59
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

stevhliu
stevhliu approved these changes Aug 7, 2024
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Nice job! Once we resolve the conflict, we can merge 🤗

@stevhliu stevhliu merged commit e0396bd into huggingface:main Aug 8, 2024
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