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sim-so merged 1 commit into from
Dec 8, 2025
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✍️ edit: TOC 하단 공백 일괄 제거 #119

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1 change: 0 additions & 1 deletion _posts/2025-09-14-Implementing-MCP-Servers-in-Python.md
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* TOC
{:toc}
<!--toc-->

_이 글은 Hugging Face 블로그의 [Implementing MCP Servers in Python: An AI Shopping Assistant with Gradio](https://huggingface.co/blog/gradio-vton-mcp)를 한국어로 번역한 글입니다._

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2 changes: 1 addition & 1 deletion _posts/2025-09-14-python-tiny-agents-study.md
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{:toc}
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이 글은 Hugging Face 블로그의 [Tiny Agents in Python: an MCP-powered agent in ~70 lines of code](https://huggingface.co/blog/python-tiny-agents)를 읽고 공부한 내용을 바탕으로 정리했습니다.
_이 글은 Hugging Face 블로그의 [Tiny Agents in Python: an MCP-powered agent in ~70 lines of code](https://huggingface.co/blog/python-tiny-agents)를 읽고 공부한 내용을 바탕으로 정리했습니다._

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## 주요 개념
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2 changes: 1 addition & 1 deletion _posts/2025-09-29-building-hf-mcp-study.md
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* TOC
{:toc}
<!--toc-->
이 글은 Hugging Face 블로그의 [Building the Hugging Face MCP Server](https://huggingface.co/blog/building-hf-mcp)를 읽고 공부한 내용을 바탕으로 정리했습니다.
_이 글은 Hugging Face 블로그의 [Building the Hugging Face MCP Server](https://huggingface.co/blog/building-hf-mcp)를 읽고 공부한 내용을 바탕으로 정리했습니다._

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1 change: 0 additions & 1 deletion _posts/2025-10-13-structured-codeagent-ko.md
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* TOC
{:toc}
<!--toc-->

_이 글은 Hugging Face 블로그의 [CodeAgents + Structure: A Better Way to Execute Actions](https://huggingface.co/blog/structured-codeagent)를 한국어로 번역한 글입니다._

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1 change: 0 additions & 1 deletion _posts/2025-10-20-2025-VLM.md
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_이 글은 Hugging Face 블로그의 [Vision Language Models (Better, Faster, Stronger)](https://huggingface.co/blog/vlms-2025)를 한국어로 번역한 글입니다._

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1 change: 0 additions & 1 deletion _posts/2025-11-02-DABStep.md
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_이 글은 Hugging Face 블로그의 [DABStep: Data Agent Benchmark for Multi-step Reasoning](https://huggingface.co/blog/dabstep)를 한국어로 번역한 글입니다._
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3 changes: 1 addition & 2 deletions _posts/2025-11-17-agent-leaderboard.md
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_이 글은 Hugging Face 블로그의 [Agent
Leaderboard: Evaluating AI Agents in Multi-Domain Scenarios](https://huggingface.co/blog/pratikbhavsar/agent-leaderboard)를 한국어로 번역한 글입니다._
_이 글은 Hugging Face 블로그의 [Agent Leaderboard: Evaluating AI Agents in Multi-Domain Scenarios](https://huggingface.co/blog/pratikbhavsar/agent-leaderboard)를 한국어로 번역한 글입니다._

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4 changes: 0 additions & 4 deletions _posts/2025-11-17-hf_translation_hub_mcp_design_and_tooling.md
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> Hugging Face 번역 MCP 서버 설계 전략 및 개발 도구는 다음과 같은 **프로젝트 목표와 운영 원칙**을 중심으로 결정되었습니다.
>
> **(1) 문서 번역 자동화 및 범용성 확보**
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1 change: 0 additions & 1 deletion _posts/2025-11-3-Welcome-GPT-OSS.md
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* TOC
{:toc}
<!--toc-->

_이 글은 Hugging Face 블로그의 [Welcome GPT OSS, the new open-source model family from OpenAI!](https://huggingface.co/blog/welcome-openai-gpt-oss)를 한국어로 번역한 글입니다._

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5 changes: 5 additions & 0 deletions _posts/2025-12-01-rteb.md
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* TOC
{:toc}
<!--toc-->
_이 글은 Hugging Face 블로그의 [Introducing RTEB: A New Standard for Retrieval Evaluation](https://huggingface.co/blog/rteb)를 한국어로 번역한 글입니다._

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# RTEB: 검색 평가의 새로운 표준

**요약 –** 여러분께 새로운 벤치마크, [RTEB(Retrieval Embedding Benchmark, 검색 임베딩 벤치마크)](https://huggingface.co/spaces/mteb/leaderboard?benchmark_name=RTEB%28beta%29)의 베타 버전을 소개합니다. RTEB는 실제 환경에 사용할 임베딩 모델의 검색 정확도를 신뢰성 있게 평가하도록 설계되었습니다. 기존 벤치마크는 진정한 일반화 능력을 측정하기 어려웠으나, RTEB는 공개 및 비공개 데이터셋을 결합한 하이브리드 전략으로 이 문제를 해결합니다. 목표는 간단합니다. 모델이 이전에 접하지 않은 데이터에서 어떻게 수행하는지 측정하기 위한, 공정하고 투명하며 응용 중심의 표준을 만드는 것입니다.
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