# model-pruning

> Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT.

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.

- Type: Skill
- Made by: Orchestra-Research
- Category: AI & agents
- Formats: Skills
- Version: 5017efe
- Source: https://github.com/orchestra-research/ai-research-skills/tree/HEAD/19-emerging-techniques/model-pruning
- Page: https://pluginboard.ai/skills/model-pruning

## Works with

- ChatGPT
- Claude
- Gemini
- GitHub Copilot
- Cursor
- Claude Code
- Codex
- Antigravity
- Gemini CLI
- Replit
- OpenClaw
- OpenCode
- Hermes Agent

## Install

### ChatGPT

In ChatGPT: Download the model-pruning folder and zip it, then Plugins → Skills → Create → Upload from your computer. Business and Enterprise plans.

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Claude

In Claude (web or desktop): Download the model-pruning folder and zip the folder itself, then upload it in Customize → Skills.

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Gemini

In Gemini: Download the model-pruning folder, then at gemini.google.com click Customize → Skills → Create → Upload and pick the folder (or a .zip of it).

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### GitHub Copilot

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.copilot/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Cursor

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.cursor/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Claude Code

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.claude/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

Or all of AI Research Skills (Orchestra), in Claude Code:

```text
/plugin marketplace add Orchestra-Research/AI-Research-SKILLs
/plugin install rag@ai-research-skills
```

### Codex

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.agents/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Antigravity

In Antigravity: Copy the model-pruning folder into ~/.gemini/config/skills (Antigravity app and IDE) or ~/.gemini/antigravity-cli/skills (Antigravity CLI).

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Gemini CLI

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.gemini/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Replit

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning .agents/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### OpenClaw

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.openclaw/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### OpenCode

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.config/opencode/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

### Hermes Agent

Run in your terminal:

```shell
npx -y degit Orchestra-Research/AI-Research-SKILLs/19-emerging-techniques/model-pruning ~/.hermes/skills/model-pruning
```

View the folder on GitHub: https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/HEAD/19-emerging-techniques/model-pruning

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From Pluginboard (https://pluginboard.ai).