model-pruning

Name: model-pruning
Rating: 1.2 (1 reviews)
Author: zechenzhangAGI

24.3

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.

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Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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Claude Code (CLI) Fast

skilz install zechenzhangAGI/AI-research-SKILLs/model-pruning

OpenCode (CLI) Fast

skilz install zechenzhangAGI/AI-research-SKILLs/model-pruning --agent opencode

OpenAI Codex (CLI) Native

skilz install zechenzhangAGI/AI-research-SKILLs/model-pruning --agent codex

Gemini CLI (Project) Project

skilz install zechenzhangAGI/AI-research-SKILLs/model-pruning --agent gemini

First time? Install Skilz: pip install skilz

Works with 14 AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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For Claude Desktop Easy

Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

Manual Installation

1. Clone the repository:

git clone https://github.com/zechenzhangAGI/AI-research-SKILLs

2. Copy the agent skill directory:

cp -r AI-research-SKILLs/19-emerging-techniques/model-pruning ~/.claude/skills/

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Need detailed installation help? Check our platform-specific guides:

Claude Desktop Guide Claude Code Guide Troubleshooting

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Agentic Skill Details

Owner: zechenzhangAGI (GitHub)
Repository: AI-research-SKILLs
Type: Non-Technical
Meta-Domain: general
Primary Domain: general
Sub-Domain: cd build pipeline
Market Score: 24.3

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