From 9f38763731178290a3a4b8a8c9999ffb9b6bd120 Mon Sep 17 00:00:00 2001
From: Ahn Joon Sung <tjdtna01@naver.com>
Date: Wed, 30 Jul 2025 00:04:30 +0900
Subject: [PATCH] =?UTF-8?q?=F0=9F=8C=90=20[i18n-KO]=20Translated=20`pipeli?=
 =?UTF-8?q?ne=5Fgradio.md`=20to=20Korean=20(#39520)?=
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* docs: ko: pipeline_gradio.md

* feat: nmt draft

* fix: manual edits

* docs: ko: pipeline_gradio.md
---
 docs/source/ko/_toctree.yml       |  4 +--
 docs/source/ko/pipeline_gradio.md | 52 +++++++++++++++++++++++++++++++
 2 files changed, 54 insertions(+), 2 deletions(-)
 create mode 100644 docs/source/ko/pipeline_gradio.md

diff --git a/docs/source/ko/_toctree.yml b/docs/source/ko/_toctree.yml
index 99f7ea8da8..19a08c300e 100644
--- a/docs/source/ko/_toctree.yml
+++ b/docs/source/ko/_toctree.yml
@@ -50,8 +50,8 @@
   - sections:
     - local: pipeline_tutorial
       title: Pipeline으로 추론하기
-    - local: in_translation
-      title: (번역중) Machine learning apps
+    - local: pipeline_gradio
+      title: 머신러닝 앱
     - local: pipeline_webserver
       title: 추론 웹 서버를 위한 파이프라인
     - local: add_new_pipeline
diff --git a/docs/source/ko/pipeline_gradio.md b/docs/source/ko/pipeline_gradio.md
new file mode 100644
index 0000000000..418ebfa0fb
--- /dev/null
+++ b/docs/source/ko/pipeline_gradio.md
@@ -0,0 +1,52 @@
+<!--Copyright 2024 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+
+⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
+rendered properly in your Markdown viewer.
+
+-->
+
+# 머신러닝 앱 [[machine-learning-apps]]
+
+머신러닝 앱을 빠르고 쉽게 구축하고 공유할 수 있는 라이브러리인 [Gradio](https://www.gradio.app/)는 [`Pipeline`]과 통합되어 추론을 위한 간단한 인터페이스를 빠르게 생성할 수 있습니다.
+
+시작하기 전에 Gradio가 설치되어 있는지 확인하세요.
+
+```py
+!pip install gradio
+```
+
+원하는 작업에 맞는 pipeline을 생성한 다음, Gradio의 [Interface.from_pipeline](https://www.gradio.app/docs/gradio/interface#interface-from_pipeline) 함수에 전달하여 인터페이스를 만드세요. Gradio는 [`Pipeline`]에 맞는 입력 및 출력 컴포넌트를 자동으로 결정합니다.
+
+[launch](https://www.gradio.app/main/docs/gradio/blocks#blocks-launch)를 추가하여 웹 서버를 생성하고 앱을 시작하세요.
+
+```py
+from transformers import pipeline
+import gradio as gr
+
+pipeline = pipeline("image-classification", model="google/vit-base-patch16-224")
+gr.Interface.from_pipeline(pipeline).launch()
+```
+
+웹 앱은 기본적으로 로컬 서버에서 실행됩니다. 다른 사용자와 앱을 공유하려면 [launch](https://www.gradio.app/main/docs/gradio/blocks#blocks-launch)에서 `share=True`로 설정하여 임시 공개 링크를 생성하세요. 더 지속적인 솔루션을 원한다면 Hugging Face [Spaces](https://hf.co/spaces)에서 앱을 호스팅하세요.
+
+```py
+gr.Interface.from_pipeline(pipeline).launch(share=True)
+```
+
+아래 Space는 위 코드를 사용하여 생성되었으며, Spaces에서 호스팅됩니다.
+
+<iframe
+	src="https://stevhliu-gradio-pipeline-demo.hf.space"
+	frameborder="0"
+	width="850"
+	height="850"
+></iframe>