ml-training-recipes
byopenraiser· 19 skills
Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.
How to install ml-training-recipes?
openraiser/nanoresearch/ml-training-recipes
$npx -y skills add openraiser/nanoresearch --skill ml-training-recipesInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/openraiser/nanoresearch" --skill "openraiser/nanoresearch/ml-training-recipes"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/openraiser/nanoresearch" that are relevant to the current task. Run `npx skills add "https://github.com/openraiser/nanoresearch"` and select the relevant skills, then follow their instructions.
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