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 accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.
- Version
- 1.0.0
- License
- MIT
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Files
- skills/model-pruning/SKILL.md
- skills/model-pruning/references/production-deployment.md
- skills/model-pruning/references/wanda.md
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