Skill UI

Compress large language models quickly using Wanda, SparseGPT, and N:M pruning to enforce hardware-friendly sparsity, enabling faster inference and deployment without retraining.

Guides ML deployment workflows by surfacing best practices, templated code, and validation steps whenever model pruning helper patterns are mentioned.

This skill covers techniques to reduce LLM size and accelerate inference using methods like Wanda and SparseGPT. It enables model compression without retraining, achieving high sparsity with minimal accuracy loss. Suitable for deploying on constrained hardware like mobile or edge devices. Includes unstructured, structured, and N:M sparsity methods.