pytorch-cuda
Configure and verify CUDA 13 readiness (toolkit, driver, and PyTorch wheel support), then run PyTorch CUDA with reliable timing and memory practices.
npx skills add majiayu000/claude-skill-registry --skill pytorch-cuda --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
--- name: pytorch-cuda description: PyTorch CUDA environment and performance guidance, with emphasis on CUDA 13 toolkit/driver requirements, PyTorch wheel compatibility, and runtime checks. Use when configuring PyTorch on NVIDIA GPUs, debugging CUDA setup, or migrating to CUDA 13; triggers: pytorch cuda, cuda 13, driver version, nvcc, torch.version.cuda, tf32, streams. --- # PyTorch CUDA ## Overview Configure and verify CUDA 13 readiness (toolkit, driver, and PyTorch wheel support), then run PyTorch CUDA with reliable timing and memory practices. ## When to Use Use this skill only when the frontmatter triggers apply; otherwise start with a standard PyTorch setup or CPU run. ## Decision Tree 1. Are you targeting CUDA 13? - Yes: verify driver minimums and toolkit availability. 2. Do you rely on prebuilt PyTorch wheels? - Yes: confirm the available CUDA builds (11.8/12.6/12.8) before upgrading. 3. Do you need GPU profiling accuracy? - Yes: use CUDA events and explicit synchronization. ## Workflows ### 1. CUDA 13 Readiness Check 1. Read the installed driver version (`nvidia-smi`). 2. Compare against CUDA 13.0 minimums (GA/Update 1/Update 2). 3. Confirm toolkit availability (`nvcc --ver
- Overview
- When to Use
- Decision Tree
- Workflows
- 1. CUDA 13 Readiness Check
- 2. PyTorch Wheel Compatibility Gate
- 3. Accurate CUDA Timing
- Non-Obvious Insights
- Evidence
- Scripts
- Dependencies
- References
What does the pytorch-cuda skill do?
Configure and verify CUDA 13 readiness (toolkit, driver, and PyTorch wheel support), then run PyTorch CUDA with reliable timing and memory practices.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill pytorch-cuda --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.