model-pruning
From the author
Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.
Install
npx skills add KalarisLabs/research-agent-skills --skill model-pruning -a claude-code
Installs to .claude/skills/model-pruning/ · Each command fetches the skill straight from GitHub with the open skills CLI.
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