🌐 [i18n-KO] Translated main_classes/deepspeed.md to Korean

docs/source/ko/_toctree.yml

@@ -288,7 +288,7 @@
       title: (번역중) Tokenizer
     - local: main_classes/trainer
       title: Trainer
-    - local: deepspeed
+    - local: main_classes/deepspeed
       title: DeepSpeed
     - local: main_classes/executorch
       title: ExecuTorch

docs/source/ko/main_classes/deepspeed.md

@@ -0,0 +1,32 @@
+<!--Copyright 2020 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.
+
+-->
+
+# DeepSpeed[[deepspeed]]
+
+Zero Redundancy Optimizer (ZeRO)로 구동되는 [DeepSpeed](https://github.com/deepspeedai/DeepSpeed)는 매우 큰 모델을 GPU에서 훈련하고 피팅하기 위한 최적화 라이브러리입니다. 여러 ZeRO 단계로 제공되며, 각 단계는 옵티마이저 상태, 기울기, 매개변수를 분할하고 CPU 또는 NVMe로의 오프로딩을 가능하게 하여 점진적으로 더 많은 GPU 메모리를 절약합니다. DeepSpeed는 [`Trainer`] 클래스와 통합되어 있으며 대부분의 설정이 자동으로 처리됩니다.
+
+그러나 [`Trainer`] 없이 DeepSpeed를 사용하려는 경우, Transformers는 [`HfDeepSpeedConfig`] 클래스를 제공합니다.
+
+<Tip>
+
+[`Trainer`]와 함께 DeepSpeed 사용에 대한 자세한 내용은 [DeepSpeed](../deepspeed) 가이드를 참조하세요.
+
+</Tip>
+
+## HfDeepSpeedConfig[[transformers.integrations.HfDeepSpeedConfig]]
+
+[[autodoc]] integrations.HfDeepSpeedConfig
+    - all