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Found 6 Skills
Run GPU workloads on Modal's serverless infrastructure. Use when the user needs remote GPU compute for training, inference, benchmarks, or batch processing and Modal CLI is available.
DGX Cloud Lepton managed GPU compute platform with run/status/cancel interface. Use when submitting TAO jobs to DGX Cloud, dispatching training/eval/inference to Lepton GPU resources, or managing Lepton workspace deployments. Trigger phrases include "run on Lepton", "submit to DGX Cloud", "Lepton job", "managed GPU on DGX Cloud".
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.
Couple Three.js WebGPU/TSL rain, snow, and wet surfaces. Use for airborne precipitation motion, physical surface deposition, persistent snow or wetness state, weather-driven ripple normals, or impact splashes.
Procedural fields for coherent scalar and vector causes in Three.js WebGPU/TSL. Use when a task needs shared causes across materials, geometry, or compute; must choose direct evaluation versus a baked field; needs deterministic CPU/TSL parity and footprint filtering; or needs metric signed-distance terrain and coast analysis.
Build or migrate Three.js WebGPURenderer, TSL node materials, and GPU compute features.