model-pruning
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 accelera
- Skills
- AI research
- 0
What it does and how to use it
A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
- No commands to memorize: you talk in plain language and the skill does the rest.
Install (Claude Code)
mkdir -p .claude/skills/model-pruning && curl -fsSL https://doutorai.pt/data/lib/skills__model-pruning.md -o .claude/skills/model-pruning/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
---
name: model-pruning
description: 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.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Emerging Techniques, Model Pruning, Wanda, SparseGPT, Sparsity, Model Compression, N:M Sparsity, One-Shot Pruning, Structured Pruning, Unstructured Pru
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