【教程贴】Docker应用-DeepSeek-R1帮助
此使用帮助适用宝塔面板9.4.0以上的版本（2025年2月6日后发布的滚动修复包，请修复面板后安装DeepSeek-R1）写在前面，配置不满足运行模型会导致服务器卡死或无法访问，请正确选择服务器配置后部署！
各模型建议的服务器配置：
实测：
2c4g可以运行1.5b，想要更流畅的话建议到8g内存，此模型可以不需要GPU
8c16g可以运行7b/8b，此模型建议使用GPU运行，建议最少使用8G运存的GPU
其他模型尚未测试，欢迎补充~
腾讯云合作伙伴性能基准测试如下：
【1.5B模型：内存占用2G左右】
2c4g（S5）：生成过程中，CPU占用100%
2c8g（S5）：生成过程中，CPU占用100%
4c16g（S2）：生成过程中，CPU占用100%
16c64g（SA2）：生成过程中，CPU占用30～40%
【7B模型：内存占用7.6G左右】
4c8g（SA2）：生成过程中，CPU占用100%
16c64g（SA2）：生成过程中，CPU占用50%
如何30秒安装一个DeepSeek-R1 AI模型？
* 首次安装可能需要1-20分钟，安装大模型服务套件总共需要下载5G以上，根据网络情况决定安装速度
如果您需要通过域名直接访问，请先到宝塔面板的【软件商店】安装Nginx，不需要域名访问则忽略
前往宝塔面板【Docker】-【应用商店】，点击DeepSeek-R1应用，点击安装即可
如果没显示DeepSeek应用，请点击右上角【更新应用列表】获取
如果需启用GPU支持，请参考此教程进行GPU设置：
https://github.com/ollama/ollama/blob/main/docs/docker.md
随后点击【已安装】应用的文件夹按钮，前往对应的应用目录
编辑docker-compose.yml文件，将第5-11行的注释去掉，保存
再回到【已安装】应用界面，将此应用重启即可启用GPU支持
【常见问题】
1、安装成功了，但无法看到DeepSeek界面，原因是什么？
安装部署完成后，软件首次启动需要花 2 - 10 分钟时间，启动完成后可以看到 Web 界面。
2、安装成功了，但是模型输出很慢，原因是什么？
模型可能会占用大量的资源(CPU/内存/GPU)，如果无法正常使用，请切换低级别的模型使用。
3、部署成功后，模型访问提示500，原因是什么？
请检查服务器内存是否足以支撑模型运行，例如：1.5b的模型需要至少1.5GB的活动内存（具体信息请查看ollama容器的日志）
4、无法访问？
注意：应用不经过系统防火墙，如果您不填写域名，勾选【允许外部访问】后是直接允许外部访问，如果您是云服务器，勾选【允许外部访问】后，请到服务器安全组放行此数据库的端口
开放安全组示例(必需)：
阿里云
腾讯云
使用遇到问题欢迎帖子留言，或者加入Docker官方交流QQ群：662047798
安装是很快，也可以正常登录，只不过没有模型选项，还需要做什么额外操作？ 我现在可以用 但是添加知识库 上传文件报错400: 'NoneType' object is not iterable 安装完成后 webui能访问 但是没有模型选择data:image/png;base64,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 模型能，在哪里，回自动下载嘛，可以改模型存放位置嘛
支持！沙发！
支持！沙发！ 学习学习 安装后，500 ：内部错误,什么问题？ 宝塔用户_pffdyr 发表于 2025-2-6 13:39安装后，500 ：内部错误,什么问题？
1.5b模型的话，服务器的活动内存需要大于1.5GB才能正常跑起来，否则ollama就会报500的错误 本帖最后由 宝塔用_9fef 于 2025-2-8 10:36 编辑
安装之后web页面访问不了 宝塔用_9fef 发表于 2025-2-8 10:31
安装之后web页面访问不了
重新安装就没有报错了。但是对外暴露端口时报错
ollama容器一直暂停中无法启动，内存也是足够的，请问什么原因
本帖最后由 nooshen 于 2025-2-9 20:49 编辑
nooshen 发表于 2025-2-8 22:46
安装是很快，也可以正常登录，只不过没有模型选项，还需要做什么额外操作？ ...
选择需要的版本，自己拉取
一直这样，什么原因呢
stone002 发表于 2025-2-9 22:17
一直这样，什么原因呢
我也是，一直这样，没人解决 cqctm 发表于 2025-2-10 08:29
我也是，一直这样，没人解决
改一下镜像就好了
https://www.bt.cn/bbs/thread-141215-1-1.html