spark-environment-setup
Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.
Install
npx skills add wshobson/agents@spark-environment-setupRuns in your terminal. Adds the skill globally for Claude Code, Cursor, Codex and others; add -g -y to skip prompts.
What it does
Spark Environment Setup DGX Spark ships a GB10 Grace Blackwell chip: aarch64 CPU, SM121 GPU, 128GB unified memory, CUDA 13. This is a narrower and younger platform than a standard x86 CUDA 12 box, so package selection and ABI matching matter more than usual — the wheel ecosystem for aarch64 + CUDA 13 is still filling in. When to Use This Skill - Setting up a fresh Spark box for training or inference. - Hitting an import error mentioning libcudart, a missing symbol, or a wheel that "installed fine but won't load." - A framework install (PyTorch, Unsloth, TRL, vLLM, xformers) fails, hangs, or…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
View source on GitHubBefore you install
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
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