Cloud Studio(云端 IDE)
选一个(试用 free)高性能workspce,约么16G显存
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.105.17 Driver Version: 525.105.17 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 On | 00000000:00:09.0 Off | 0 |
| N/A 48C P8 15W / 70W | 5MiB / 15360MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
部署gemma3
16G的显存,选了12b的模型 ollama install,要是显存够用,模型size往上堆就完了
cloud studio workspace内置ollama服务,下载
ollama run gemma3:12b
如遇到ollama 错误
writing manifest
success
Error: llama runner process has terminated: this model is not supported by your version of Ollama. You may need to upgrade
需要升级内置的ollama版本,到v0.6.0
# 停止当前运行的 Ollama 服务
sudo systemctl stop ollama
# 下载最新安装脚本并重装
curl -fsSL https://ollama.ai/install.sh | sh
# 重启服务
sudo systemctl start ollama
查看ollama版本和model(需要重启)
绑定域名+端口映射
腾讯云CloudStudio:喂饭教程:10分钟部署一个DeepSeek,支持网页调用!关键还免费!
总结
这一套方案是将cloud studio的高性能工作空间做成了ollama service,并将本地ollama的端口映射到了公网域名,可以外部访问。