Is huggingface-zerogpu safe?
Grade A, 98/100. No meaningful risk found.
AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.
Ahuggingface-zerogpu
skills/huggingface-zerogpu98/100 · No meaningful risk found1 low
huggingface-zerogpu
skills/huggingface-zerogpuAI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.
- Content hash
- sha256:e4519bc1a792b58f201625139270c67c9e844d667d00020954b2f975864bd34e
- Files
- 5
- Quality
- 100/100
Security findings
- lowHides actions from the userSL102 · skills/huggingface-zerogpu/SKILL.md:81
Do not run inference or CUDA kernels at module scope — the real GPU is not attached, so operations either silently run on CPU or fail.The skill asks the agent to act without the user's knowledge. Fix: Every side effect should be visible to the user. Remove the concealment instruction. Severity lowered: the line reads as documentation, not an instruction.
Files in this skill
- SKILL.md17.8 KB
- references/concurrency.md2.5 KB
- references/cuda-and-deps.md4.7 KB
- references/how-quota-works.md3.8 KB
- references/how-zerogpu-works.md4.7 KB
Questions about huggingface-zerogpu
- Is huggingface-zerogpu safe to install?
- Our scanner gave huggingface-zerogpu grade A (98/100): no meaningful risk found. It matched 1 rule(s); review them below before installing. Static analysis cannot prove safety, so pin the reviewed revision with a lockfile.
- How do I install huggingface-zerogpu in Claude Code or Codex?
- Run skillhash add github:huggingface/skills/skills/huggingface-zerogpu. It downloads the exact commit, checks the grade against your policy, writes skills.lock and installs it into .claude/skills and .agents/skills.
- What happens if huggingface-zerogpu changes upstream?
- Its content hash changes. skillhash verify fails in CI until you review the new version and update the lock. With a watch, you also get an alert.
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