Optimize CoreML models for iOS and macOS deployment. Covers quantization, palettization, pruning, Neural Engine targeting, compute unit selection, and performance profiling. Use when converting ML models to CoreML, optimizing model size/latency, debugging Neural Engine issues, or benchmarking on-device inference.
How to install coreml-optimizer?
ckorhonen/claude-skills/coreml-optimizer
$npx -y skills add ckorhonen/claude-skills --skill coreml-optimizerInstalls into the current project.
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Run `npx skills use "https://github.com/ckorhonen/claude-skills" --skill "ckorhonen/claude-skills/coreml-optimizer"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/ckorhonen/claude-skills" that are relevant to the current task. Run `npx skills add "https://github.com/ckorhonen/claude-skills"` and select the relevant skills, then follow their instructions.
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