SKILL
emerging-techniques-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.
Target: Learning & research. Automatically collected · unverified.
Use with Cursor
A guide for this combination is not available yet, and compatibility has not been verified.
Requirements
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