wanda

Wanda prunes LLMs by weight magnitude × input activation, achieving 50% sparsity with <1% accuracy loss, no retraining required.

Skills
AI research
2

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/wanda && curl -fsSL https://doutorai.pt/data/lib/skills__wanda.md -o .claude/skills/wanda/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Wanda: Pruning by Weights and Activations

Based on ICLR 2024 paper (arXiv 2306.11695) - A Simple and Effective Pruning Approach for Large Language Models

## Overview

**Source**: https://arxiv.org/abs/2306.11695
**Conference**: ICLR 2024
**GitHub**: https://github.com/locuslab/wanda

Wanda prunes LLMs by weight magnitude × input activation, achieving 50% sparsity with <1% accuracy loss, no retraining required.

## Core Innovation

### Pruning Criterion

**Key insight**: Weight importance = magnitude × usage

```python
importance(w_ij) = |w_ij| × ||X_i||

where:
- w_ij: Weight connecting in

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