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@@ -1,4 +1,62 @@
 # 部署模型到 Gitee AI 算力
 
+本教程将以模型 [stabilityai/stable-diffusion-2-base](https://ai.gitee.com/hf-models/stabilityai/stable-diffusion-2-base) 为例，逐步讲解如何将模型部署到 Gitee AI 算力上并用于图像生成。
 
-TODO
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+## 1. 进入模型引擎新建页面
+
+点击导航栏中的「解决方案」菜单，点击「模型引擎」进入模型引擎页面，然后点击右侧的「+新建模型引擎」按钮：
+
+![step1-1](/static/img/engines/model-engine/getting-started/step1-1.png)
+
+或者，你也可以在模型页面中通过筛选找到 [stabilityai/stable-diffusion-2-base](https://ai.gitee.com/hf-models/stabilityai/stable-diffusion-2-base) :
+
+![step1-2](/static/img/engines/model-engine/getting-started/step1-2.png)
+
+点击它的资料卡片进入主页了解详细信息，然后在「部署」菜单中点击「模型引擎」以将它部署为模型引擎。
+
+![step1-3](/static/img/engines/model-engine/getting-started/step1-3.png)
+
+## 2. 填入模型名称和你的模型引擎名称
+
+![step2](/static/img/engines/model-engine/getting-started/step2.png)
+
+## 3. 选择你的算力资源配置
+
+选择算力供应商、区域以及资源类型。
+
+![step3](/static/img/engines/model-engine/getting-started/step3.png)
+
+该界面展示了每种算力的配置和每小时单价，你可以根据模型的算力需求和预算选择合适的算力。
+
+## 4. 自定义你的模型引擎
+
+目前可自定义的配置有：
+
+- **版本：** 可填入模型的 Git 仓库中的分支名、标签名和提交（commit sha）。未指定版本时，模型引擎会从模型仓库的主分支上拉取最新的文件。
+- **任务：** 在你选择模型后，该配置项会自动变更为合适的任务，如果你选择的模型支持多种任务且想使用其它任务，则可以更改该配置项。
+
+![step4](/static/img/engines/model-engine/getting-started/step4.png)
+
+## 5. 创建你的模型引擎
+
+点击「新建模型引擎」按钮。
+
+![step5](/static/img/engines/model-engine/getting-started/step5.png)
+
+## 6. 等待模型引擎下载模型、初始化和运行
+
+模型引擎从创建到运行会经历三个阶段：等待分配算力资源、下载模型仓库、加载模型。等待时间取决于模型的大小，对于比较大的模型，大部分时间会花费在模型下载上，你可以参考服务器信息中的下载进度来了解大概的剩余等待时间。
+
+![step6](/static/img/engines/model-engine/getting-started/step6.png)
+
+## 7. 测试你的模型引擎
+
+在「文本转图像」界面中输入任意提示词然后点击运行即可测试模型引擎的运行效果。
+
+![step7](/static/img/engines/model-engine/getting-started/step7.png)
+
+## 8. 在你的应用程序中调用模型引擎
+
+模型引擎是以 API 的形式提供服务的，你可以参考「调用示例」中给出的示例代码为你的应用程序添加模型引擎的调用能力。
+
+![step8](/static/img/engines/model-engine/getting-started/step8.png)
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