Neural Model Optimization
CommunityCompress models for real-world deployment.
Authorlucifertrj
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Large ML models are expensive to run and hard to deploy at scale; this skill demonstrates how to compress models while preserving usable performance for real-world applications.
Core Features & Use Cases
- Distillation to transfer knowledge from large to smaller models
- Pruning to remove redundant parameters
- Quantization to reduce precision and memory footprint
- Real-world deployment scenarios including edge devices, mobile apps, and cloud services
Quick Start
Design a compact inference pipeline for a given model.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Neural Model Optimization Download link: https://github.com/lucifertrj/skills-based-app/archive/main.zip#neural-model-optimization Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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