Translate Hugging Face blog post: Building Blocks for Foundation Model Training and Inference on AWS

[Jwaminju]

Source: https://huggingface.co/blog/amazon/foundation-model-building-blocks

This PR adds a Korean translation draft for foundation-model-building-blocks.

Downstream handoff:

• SEO review should use the translation-flow manifest.
• Quality review should use the translation-flow manifest.

[github-actions]

PR Preview Action v1.8.1
🚀 View preview at https://hugging-face-krew.github.io/pr-preview/pr-131/
Built to branch gh-pages at 2026-07-28 13:59 UTC. Preview will be ready when the GitHub Pages deployment is complete.

[github-actions]

HF Agent Review

Gate	Result
Quality	✅ Pass
SEO	✅ Pass

Head SHA: 7a03a9fa1188f6519818dfe2177544e82baef6dc

Quality report — ✅ Pass

Quality Report

• Status: review_required
• Quality Score: 79.0
• Hard failures: 0
• Issues: 9
• Source available: True
• Source changed: False
• Source segments: 1
• Target segments: 80

Scorecard

Dimension	Score
adequacy	60.0
technical_accuracy	100.0
completeness	80.0
terminology	60.0
fluency	85.0
publishing_integrity	100.0
style_locale	60.0

Metrics

• qe_metric: heuristic
• cache_hits: 0
• cache_misses: 0
• warning: Source was fetched as HTML text; structural hard gates, segment coverage, and segment metrics were skipped.

MQM Judge

• Enabled: True
• Provider: openai
• Model: gpt-5.6-luna
• Reasoning effort: none
• Prompt: /home/runner/work/hugging-face-krew.github.io/hugging-face-krew.github.io/workflow/skills/quality/judges/mqm_prompt.md
• Requested segments: 0
• Evaluated segments: 0
• MQM errors: 0
• Cache hits: 0
• Cache misses: 0
• warning: MQM judge skipped: no source/target segment alignment is available.
• warning: MQM judge skipped: source was fetched as HTML text, not comparable Markdown segments.

Style Guide

• Enabled: True
• Guide: /home/runner/work/hugging-face-krew.github.io/hugging-face-krew.github.io/workflow/skills/quality/style/hf-blog-ko-translation-guide.md
• Policy: /home/runner/work/hugging-face-krew.github.io/hugging-face-krew.github.io/workflow/skills/quality/configs/style_policy.yml
• Style score: 60.0
• Rule hits: {'first_mention_bilingual': 1, 'intro_closing_style': 1, 'modal_strength': 4, 'translationese': 1}

Style Guide Findings

Rule	Severity	Segment	Current	Suggested
translationese	minor		에 의해	Rewrite the sentence in natural Korean.
intro_closing_style	minor	p_002	이 포스트	Rewrite the intro or closing in natural Korean blog style.
modal_strength	major	h_001	AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소	Preserve the strength of may using: 수 있습니다, 일 수 있습니다.
modal_strength	major	h_001	AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소	Preserve the strength of can using: 수 있습니다.
modal_strength	major	h_001	AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소	Preserve the strength of must using: 반드시, 해야 합니다.
modal_strength	major	h_001	AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소	Preserve the strength of up to using: 최대.
first_mention_bilingual	minor		미세 조정	Use 미세 조정(fine-tuning) on first mention, then 미세 조정 afterward.

Issues

QL-001 terminology / major

• Message: Product or library name was not preserved.
• Source: Transformers
• Suggested fix: Preserve Transformers exactly.
• Reason: Glossary policy requires preserving this product/library/model term.

QL-002 fluency / minor

• Message: Translationese expression found.
• Target: 에 의해
• Suggested fix: Rewrite the sentence in natural Korean.
• Reason: The style guide lists this expression as translationese to avoid.

QL-003 style_locale / minor

• Message: Intro or closing phrasing sounds mechanically translated.
• Target: 이 포스트
• Suggested fix: Rewrite the intro or closing in natural Korean blog style.
• Reason: The style guide recommends natural Korean openings and closings over mechanical source phrasing.

QL-004 accuracy / major

• Message: Modal or certainty strength may have changed.
• Source: may
• Target: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Suggested fix: Preserve the strength of may using: 수 있습니다, 일 수 있습니다.
• Reason: The style guide requires preserving may/can/should/must/up to/in some cases/not always strength.

QL-005 accuracy / major

• Message: Modal or certainty strength may have changed.
• Source: can
• Target: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Suggested fix: Preserve the strength of can using: 수 있습니다.
• Reason: The style guide requires preserving may/can/should/must/up to/in some cases/not always strength.

QL-006 accuracy / major

• Message: Modal or certainty strength may have changed.
• Source: must
• Target: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Suggested fix: Preserve the strength of must using: 반드시, 해야 합니다.
• Reason: The style guide requires preserving may/can/should/must/up to/in some cases/not always strength.

QL-007 accuracy / major

• Message: Modal or certainty strength may have changed.
• Source: up to
• Target: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Suggested fix: Preserve the strength of up to using: 최대.
• Reason: The style guide requires preserving may/can/should/must/up to/in some cases/not always strength.

QL-008 terminology / minor

• Message: First mention is missing the recommended bilingual term.
• Source: fine-tuning
• Target: 미세 조정
• Suggested fix: Use 미세 조정(fine-tuning) on first mention, then 미세 조정 afterward.
• Reason: The style guide recommends preserving searchability by adding English in parentheses on first mention.

QL-009 accuracy / major

• Message: Semantic adequacy evaluation is incomplete.
• Suggested fix: Complete MQM evaluation for every aligned segment before auto-passing.
• Reason: Heuristic QE only checks surface signals and cannot establish semantic equivalence.

SEO report — ✅ Pass

SEO Eval Report

Gate: ✅ PASS — deterministic AND rubric

• File: ../target/_posts/2026-05-12-foundation-model-building-blocks.md
• Source: —
• Primary keyword: (none — D5 skipped)
• Mode: file

Gate

• Status: PASS
• Blockers: ✅ pass
• Deterministic REQUIRED (D1–D7): ✅ pass
• Rubric (R1–R6): ✅ pass (mean None, min None)

Blockers

✅ body_not_empty: Body is not empty
✅ robots_indexable: Robots is indexable
✅ internal_links_resolve: All internal links resolve
✅ local_images_resolve: All local images resolve

Required checks (gated)

✅ heading_hierarchy: Heading hierarchy: Valid

OpenAI rubric checks

✅ semantic_metadata: PASS (required) — 타이틀, 설명, 렌더링된 H1 및 목차/헤딩들이 모두 AWS에서 Foundation Model 학습 및 추론에 필요한 구성 요소를 다루며 의미적으로 일치한다. 번역 표기를 포함한 오프닝도 주제에 부합한다.
✅ alt_semantics: PASS (review) — No images provided; non-empty alt text assessment not applicable.

Advisory checks (not gated)

✅ opening_summary: Opening 3 paragraphs: 726 chars (recommend ≥150 for KO/GEO)
✅ h1_count: Markdown H1 count: 1 (review against rendered layout)
✅ citations: Citations/statistics: 93 (recommend ≥1 for GEO)
⚠️ question_headings: Scannable H2/H3 (question or keyword): 0 (0 question, 0 keyword)
⚠️ internal_links: Internal links: 0 (recommend 2-3)
✅ word_count: Body length: 22601 chars (recommend ≥800 for KO)
ℹ️ primary_keyword: No primary_keyword in manifest — keyword check skipped
ℹ️ no_images: No images found (optional)

Signals (evidence — not directly gated)

• Frontmatter: title 40 chars, description 71 chars, author present True
• Title text: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Description text: AWS 기반 Foundation Model 학습과 추론 인프라를 구성하는 컴퓨트, 네트워크, 스토리지, 운영 요소를 정리합니다.
• Opening text: * TOC
  {:toc}

이 글은 Hugging Face 블로그의 Building Blocks for Foundation Model Training and Inference on AWS를 한국어로 번역한 글입니다.

• Opening: first paragraph 202 chars, first 3 paragraphs 726 chars
• Headings: markdown H1 1, rendered effective H1 2, layout title H1 True
• Links: total 91, external 91, internal 0, citation signals 93
• Images: total 0, empty alt 0, filename-like alt 0, missing local files 0

Semantic review packet

• Title: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Description: AWS 기반 Foundation Model 학습과 추론 인프라를 구성하는 컴퓨트, 네트워크, 스토리지, 운영 요소를 정리합니다.
• Rendered H1 candidates: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소, AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• Opening: * TOC
  {:toc}

이 글은 Hugging Face 블로그의 Building Blocks for Foundation Model Training and Inference on AWS를 한국어로 번역한 글입니다.

• Canonical/permalink: —
• Instruction: Compare title, description, rendered H1, and opening text for meaning consistency. This packet is evidence only; it does not decide pass/fail.

Frontmatter (advisory — written by metadata step, not gated)

✅ title: Title: 40 chars (recommend ≤60)
✅ description: Description: 71 chars (semantic quality reviewed separately)
✅ image: OG image: assets/images/blog/posts/2026-05-12-foundation-model-building-blocks/thumbnail.png
✅ categories: Categories: 2 (recommend 2-3)
✅ author: Author: dailybot

SEO metadata suggestion — PARTIAL

This is a suggestion. SEO is applied only when the post frontmatter is updated.
To apply safe fields from a partial suggestion, leave a trusted PR comment: metadata apply.

• Auto apply: False
• Requires human: True
• Mode: frontmatter_only
• Reason: metadata candidate needs policy decisions or missing title/description

Candidate

• title: AWS에서 Foundation Model 학습 및 추론을 위한 구성 요소
• description: AWS 기반 Foundation Model 학습과 추론 인프라를 구성하는 컴퓨트, 네트워크, 스토리지, 운영 요소를 정리합니다.
• categories: ['Translation', 'HuggingFace']
• image: assets/images/blog/posts/2026-05-12-foundation-model-building-blocks/thumbnail.png

Needs policy decision

• target_url
• source_url
• canonical_policy
• translation_indexing
• target_locale
• source_locale

Warnings

• None