model-pruning
关于
This skill provides one-shot pruning techniques like Wanda and SparseGPT to compress LLMs without retraining, reducing model size by 40-60% with minimal accuracy loss. It enables faster inference on hardware accelerators by implementing various sparsity patterns, including unstructured, structured, and N:M pruning. Use it to deploy models on constrained hardware or achieve 2-4× inference speedups.
快速安装
Claude Code
推荐npx skills add davila7/claude-code-templates -a claude-code/plugin add https://github.com/davila7/claude-code-templatesgit clone https://github.com/davila7/claude-code-templates.git ~/.claude/skills/model-pruning在 Claude Code 中复制并粘贴此命令以安装该技能
GitHub 仓库
Frequently asked questions
What is the model-pruning skill?
model-pruning is a Claude Skill by davila7. Skills package instructions and resources that Claude loads on demand, so Claude can perform model-pruning-related tasks without extra prompting.
How do I install model-pruning?
Use the install commands on this page: add model-pruning to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does model-pruning belong to?
model-pruning is in the Other category, tagged Emerging Techniques, Model Pruning, Wanda, SparseGPT, Sparsity and Model Compression.
Is model-pruning free to use?
Yes. model-pruning is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
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