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* docs: add Chinese readme * fix: cleanup docs
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‎README.md

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<p align="center">
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<h3 align="center">Easy Model Deployer: Simple, Efficient, and Easy-to-Integrate</h3>
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<h3 align="center">Easy Model Deployer: Easy Foundation Model Hosting on AWS</h3>
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</p>
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<p align="center">
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<a href="README.md"><strong>English</strong></a> |
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<a href="README_zh.md"><strong>简体中文</strong></a>
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</p>
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<p align="center">
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<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-yellowgreen.svg" alt="MIT License"></a>
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<a href="https://pypi.org/project/easy_model_deployer"><img src="https://img.shields.io/pypi/v/easy_model_deployer.svg?logo=pypi&label=PyPI&logoColor=gold"></a>
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<a href="https://pypi.org/project/easy_model_deployer"><img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dw/easy-model-deployer"></a>
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<a href="https://pypi.org/project/easy_model_deployer"><img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dw/easy_model_deployer"></a>
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<a href="https://github.com/aws-samples/easy-model-deployer/actions/workflows/release-package.yml"><img src="https://github.com/aws-samples/easy-model-deployer/actions/workflows/release-package.yml/badge.svg" alt="Build Status"></a>
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</p>
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## 🔥 Latest News
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- 2025-04-29: Deploy Qwen 3 series models with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md##famous-models###Qwen-3-Series).
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- 2025-04-21: Deploy GLM Z1/0414 series models with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md##famous-models###GLM-Z1/0414-Series).
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- 2025-03-17: Deploy Gemma 3 series models with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md##famous-models###gemma-3-series).
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- 2025-03-06: Deploy QwQ-32B with [one command line](docs/en/best_deployment_practices.md##famous-models###qwen-series###qwq-32b).
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- 2024-04-29: Deploy Qwen 3 series models with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#qwen-3-series).
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- 2024-04-21: Deploy GLM Z1/0414 series models with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#glm-z1-0414-series).
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- 2024-03-17: Deploy Gemma 3 series models with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#gemma-3-series).
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- 2024-03-06: Deploy QwQ-32B with [one command line](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#qwen-series#qwq-32b).
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## Introduction
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- Different instance types (CPU/GPU/AWS Inferentia)
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- Convenient integration (OpenAI Compatible API, LangChain client, etc.)
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## Support Models
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<details>
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<summary>Deepseek Reasoning Model</summary>
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<a href="https://github.com/deepseek-ai/DeepSeek-R1"><strong>DeepSeek-R1-Distill-Qwen-14B</strong></a>
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## Supported Models
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Easy Model Deployer supports a wide range of models including:
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- **LLMs**: Qwen, Llama, DeepSeek, GLM, InternLM, Baichuan, and more
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- **Vision-Language Models**: Qwen-VL, InternVL, Gemma3-Vision, and more
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- **Embedding Models**: BGE, Jina, BERT-based models
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- **Reranking Models**: BGE-Reranker, Jina-Reranker
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- **ASR Models**: Whisper variants
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- **Custom Models**: Support for custom Docker images
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</details>
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For the complete list of supported models and deployment configurations, see [Supported Models](docs/en/supported_models.md).
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## 🔧 Get Started
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Invoke the deployed model for testing by CLI.
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```bash
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emd invoke DeepSeek-R1-Distill-Qwen-1.5B
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emd invoke <ModelId>
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```
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> **💡 Tip** You can find the *ModelId* in the output by `emd status`.
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> **💡 Tip** You can find the *ModelId* in the output by `emd status`. For example: `emd invoke DeepSeek-R1-Distill-Qwen-1.5B`
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- [Integration examples](https://aws-samples.github.io/easy-model-deployer/)
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- [EMD client](docs/en/emd_client.md)
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### List Supported Models
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Quickly see what models are supported, this command will output all information related to deployment. (Plese browse [Supported Models](docs/en/supported_models.md) for more information.)
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Quickly see what models are supported, this command will output all information related to deployment. (Please browse [Supported Models](docs/en/supported_models.md) for more information.)
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```bash
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emd list-supported-models
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Delete the deployed model.
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```bash
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emd destroy DeepSeek-R1-Distill-Qwen-1.5B
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emd destroy <ModelId>
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```
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> **💡 Tip** You can find the *ModelId* in the output by `emd status`.
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> **💡 Tip** You can find the *ModelId* in the output by `emd status`. For example: `emd destroy DeepSeek-R1-Distill-Qwen-1.5B`
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## 📖 Documentation
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‎README_zh.md

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<p align="center">
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<h3 align="center">Easy Model Deployer: 大模型上云，一键搞定</h3>
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</p>
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<p align="center">
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<a href="README.md"><strong>English</strong></a> |
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<a href="README_zh.md"><strong>简体中文</strong></a>
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</p>
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<p align="center">
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<a href="https://aws-samples.github.io/easy-model-deployer/en/installation"><strong>文档</strong></a> ·
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<a href="https://github.com/aws-samples/easy-model-deployer/releases"><strong>更新日志</strong></a>
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</p>
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<p align="center">
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<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-yellowgreen.svg" alt="MIT License"></a>
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<a href="https://pypi.org/project/easy_model_deployer"><img src="https://img.shields.io/pypi/v/easy_model_deployer.svg?logo=pypi&label=PyPI&logoColor=gold"></a>
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<a href="https://pypi.org/project/easy_model_deployer"><img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dw/easy_model_deployer"></a>
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<a href="https://github.com/aws-samples/easy-model-deployer/actions/workflows/release-package.yml"><img src="https://github.com/aws-samples/easy-model-deployer/actions/workflows/release-package.yml/badge.svg" alt="Build Status"></a>
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</p>
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## 🔥 最新动态
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- 2024-04-29: 通过[一行命令](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#qwen-3-series)部署 Qwen 3 系列模型。
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- 2024-04-21: 通过[一行命令](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#glm-z1-0414-series)部署 GLM Z1/0414 系列模型。
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- 2024-03-17: 通过[一行命令](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#gemma-3-series)部署 Gemma 3 系列模型。
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- 2024-03-06: 通过[一行命令](https://github.com/aws-samples/easy-model-deployer/blob/main/docs/en/best_deployment_practices.md#famous-models#qwen-series#qwq-32b)部署 QwQ-32B。
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## 简介
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还在为大模型部署而头疼吗？Easy Model Deployer 让你告别复杂的环境配置，轻松将**开源大模型**（[支持的模型](docs/en/supported_models.md)）部署到 AWS 云端。
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无论是大语言模型、视觉模型还是自定义模型，一条命令即可搞定部署。更棒的是，部署完成后直接获得 **OpenAI 兼容 API** 和 [**LangChain 接口**](https://github.com/langchain-ai/langchain)，让你的 AI 应用开发如虎添翼。
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专为追求高效、稳定模型服务的开发者打造，让技术门槛不再成为创新的阻碍。
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![cli](docs/images/demo.avif)
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**核心特性**
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- 一键部署模型到 AWS（Amazon SageMaker、Amazon ECS、Amazon EC2）
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- 多样化模型类型（大语言模型、视觉语言模型、嵌入模型、视觉模型等）
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- 丰富的推理引擎（vLLM、TGI、Lmdeploy 等）
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- 不同实例类型（CPU/GPU/AWS Inferentia）
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- 便捷集成（OpenAI 兼容 API、LangChain 客户端等）
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## 支持的模型
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Easy Model Deployer 支持广泛的模型类型，包括：
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- **大语言模型**: Qwen、Llama、DeepSeek、GLM、InternLM、Baichuan 等
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- **视觉语言模型**: Qwen-VL、InternVL、Gemma3-Vision 等
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- **嵌入模型**: BGE、Jina、基于 BERT 的模型
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- **重排序模型**: BGE-Reranker、Jina-Reranker
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- **语音识别模型**: Whisper 变体
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- **自定义模型**: 支持自定义 Docker 镜像
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完整的支持模型列表和部署配置，请参见[支持的模型](docs/en/supported_models.md)。
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## 🔧 快速开始
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### 安装
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通过 PyPI 安装 Easy Model Deployer，目前支持 Python 3.9 及以上版本：
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```bash
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pip install easy-model-deployer
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emd
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```
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### 初始化
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准备模型部署所需的基础资源。
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更多信息请参考[架构说明](https://aws-samples.github.io/easy-model-deployer/en/architecture/)。
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```bash
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emd bootstrap
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```
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> **💡 提示** 通过 `pip` 升级 EMD 后，需要重新运行此命令来更新环境。
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### 部署模型
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通过交互式 CLI 或一行命令部署模型。
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```bash
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emd deploy
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```
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> **💡 提示** 要查看所有可用参数，请运行 `emd deploy --help`。
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> 当您看到 "Waiting for model: ..." 消息时，表示部署任务已开始，您可以按 `Ctrl+C` 停止终端输出。
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>
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> - 有关部署参数的更多信息，请参考[部署参数](docs/en/installation.md)。
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> - 有关使用命令行参数的最佳实践示例，请参考[最佳部署实践](docs/en/best_deployment_practices.md)。
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### 查看状态
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检查模型部署任务的状态。
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emd status
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```
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> **💡 提示** EMD 允许同时启动多个部署任务。
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### 调用模型
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通过 CLI 调用已部署的模型进行测试。
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emd invoke <ModelId>
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```
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> **💡 提示** 您可以在 `emd status` 的输出中找到 *ModelId*。例如：`emd invoke DeepSeek-R1-Distill-Qwen-1.5B`
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- [集成示例](https://aws-samples.github.io/easy-model-deployer/)
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- [EMD 客户端](docs/en/emd_client.md)
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- [Langchain 接口](docs/en/langchain_interface.md)
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- [OpenAI 兼容接口](docs/en/openai_compatiable.md)
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> **💡 提示** OpenAI 兼容 API 仅支持 Amazon ECS 和 Amazon EC2 部署类型。
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### 列出支持的模型
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快速查看支持哪些模型，此命令将输出与部署相关的所有信息。（更多信息请浏览[支持的模型](docs/en/supported_models.md)。）
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```bash
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```
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### 删除模型
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删除已部署的模型。
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```bash
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emd destroy <ModelId>
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```
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> **💡 提示** 您可以在 `emd status` 的输出中找到 *ModelId*。例如：`emd destroy DeepSeek-R1-Distill-Qwen-1.5B`
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## 📖 文档
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有关高级配置和详细指南，请访问我们的[文档网站](https://aws-samples.github.io/easy-model-deployer/)。
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## 🤝 贡献
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我们欢迎贡献！请查看 [CONTRIBUTING.md](CONTRIBUTING.md) 了解指南。

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