Model Pruning
Skill Verified ActiveReduce 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.
To reduce LLM size and accelerate inference using techniques like Wanda and SparseGPT, enabling deployment on constrained hardware and efficient serving.
Features
- Reduce model size by 40-60%
- Accelerate inference with hardware-friendly sparsity
- Deploy on constrained hardware
- Compress models without retraining (one-shot)
- Implement Wanda, SparseGPT, and N:M structured pruning
Use Cases
- Compressing LLMs for deployment on edge devices
- Achieving faster inference speeds on hardware accelerators
- Reducing memory footprint for efficient LLM serving
- Exploring state-of-the-art model pruning techniques
Non-Goals
- Retraining models after pruning
- Providing a general-purpose model optimization suite
- Handling unstructured sparsity without hardware support for speedup
Practical Utility
- info:Edge casesThe SKILL.md names limitations like 'no retraining' and 'activation dependency' but does not detail specific failure modes with symptoms and recovery steps.
Execution
- info:ValidationWhile the code uses standard Python libraries, explicit schema validation for all inputs and outputs is not detailed in the documentation.
- info:Pinned dependenciesDependencies are listed, but specific version pinning or lockfiles are not explicitly shown in the documentation for the provided examples.
Code Execution
- info:Error HandlingPython scripts generally handle errors, but specific details on structured error reporting or fail-closed behavior for the pruning functions are not explicitly documented.
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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