dsh-wsl-gpu
DeepSeek Harness 工具：WSL 的 GPU/VRAM 诊断工具 — nvidia-smi、Blackwell 提示、推理端口冲突。
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add github:173787247/dsh-wsl-gpu#b225fd41c4ef97e0f5807381ad16a87843fb7c24Wsl Gpu 以 dsh-wsl-gpu 发布，当前版本为 0.2.2。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
Install set: part of dsh-wsl-kit. Prefer
KIT_SET=daily|llm|github|full(see kit README). Fault tree: TROUBLESHOOTING.md.
DeepSeek Harness tool: gpu_doctor — WSL nvidia-smi, VRAM pressure, Blackwell/5080 hints, and whether Ollama / vLLM / Unsloth Desktop ports compete on one GPU.
Part of dsh-wsl-kit.
| Field | Value |
|---|---|
| Plugin | dsh-wsl-gpu 0.2.1 |
| Minimum dsh | ≥ 0.1.2 (web UI one-shot ?token= on Windows relay :3081) |
| Latest verified | See dsh-wsl-kit Compatibility (currently 0.1.5-rc.1) — single source of truth for the suite |
| Kit set | llm / full (some also useful alone) |
| Cloud Flash | Use model id deepseek-flash (V4.1 Flash) in ~/.dsh/settings.yaml / llm-deepseek — not configured by this plugin |
| Agent Teams | Upstream experimental; not required here |
Suite floor versions: kit check-plugin-versions.sh. Fault tree: TROUBLESHOOTING.md.
Local inference needs the Windows NVIDIA driver to expose GPUs into WSL2. On a single ~16GB card (e.g. RTX 5080), opening Ollama and llama-server and vLLM at once is a common OOM path. This tool reports visibility, VRAM, and open inference ports together.
curl -fsSL https://raw.githubusercontent.com/173787247/dsh-wsl-kit/master/install.sh | KIT_SET=llm bash
# or:
dsh plugin --profile web add github:173787247/dsh-wsl-gpu
Ask: “Run gpu_doctor” after driver updates, CUDA build failures, or before loading another large GGUF.
sm_120, CUDA 12.8+/13.x)11434 / 1234 / 8000 / 8080host_reach and docker_doctor focus=vllm- id: dsh-wsl-gpu
name: dsh-wsl-gpu
config:
timeoutMs: 20000
probeTimeoutMs: 1200
probeInference: true
npm test
MIT