quant-recipe-search
OfficialFind optimal quantization recipes for models
AuthorNVIDIA
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps users find the best quantization strategy for a model by turning optimization goals, accuracy constraints, and performance targets into a structured recipe search process.
Core Features & Use Cases
- Recipe Search Strategy: Designs iterative quantization experiments across formats, calibration methods, module selections, and runtime constraints.
- Candidate Evaluation Planning: Establishes baselines, comparison criteria, and promotion rules for selecting validated optimization recipes.
- Use Case: Optimize a large language model for inference throughput or memory reduction by exploring ModelOpt quantization candidates while preserving benchmark quality.
Quick Start
Use the quant-recipe-search skill to find the best quantization recipe for my model with a focus on throughput, memory usage, and benchmark accuracy.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 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: quant-recipe-search Download link: https://github.com/NVIDIA/Model-Optimizer/archive/main.zip#quant-recipe-search Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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