huggingface-zerogpu
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.
Target: Software development & testing. Automatically collected · unverified.
Excerpt from the author’s documentation
Extracted from a fixed version of SKILL.md in its original language. This is the author’s documentation; installation, compatibility and runtime results have not been verified by this site.
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Topics in the source
- Hugging Face ZeroGPU
- Scope
- Reference Files
- Hardware
- Basic Pattern
- CUDA Availability Model
- Device selection idiom still works
- Eager loading is the right default
Rules and patterns for ML demos on Hugging Face Spaces with ZeroGPU hardware. Covers @spaces.GPU, duration and quota tuning, process isolation, the CUDA availability model, concurrency safety, and CUDA build constraints. This skill is for Gradio SDK Spaces using ZeroGPU hardware. Docker and Static Spaces cannot schedule onto ZeroGPU, and Streamlit apps now run as Docker Spaces — so this skill applies only to Gradio. For general Gradio coding (components, layouts, event listeners), see the huggingface-gradio skill in this repo. The authoritative ZeroGPU docs live at https://huggingface.co/docs/hub/spaces-zerogpu — refer to them for the current backing GPU, runtime version lists, and tier thresholds, all of which change over time. | Reference | When to read | |-----------|--------------| | references/concurrency.md | Always read alongside SKILL.md when writing ZeroGPU code — handlers run in parallel by default | | references/how-zerogpu-works.md | When reasoning about cold-starts, worker reuse, why module-scope warmup does not carry to requests, or why returning CUDA tensors hangs | | references/how-quota-works.md | When choosing duration values, debugging illegal duration vs quota e
This is an excerpt. Refer to the complete source and its current requirements.
- Source repository
- huggingface/skills
- Source file
- skills/huggingface-zerogpu/SKILL.md
- Fixed revision
- 25910b3d0ba31a2ba102f901cdc9e008c278a69c
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This record was collected automatically. Its documentation, suitability and runtime behavior have not been manually verified.
Author: huggingface/skills · original repository metadata. Documentation review: Not reviewed. Last source check: 2026-11-09T16:01:02.765Z.
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