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.
Quickly install coreml-optimizer AI skill to your development environment via command line
Source: ckorhonen/claude-skills.
Expert guidance for optimizing machine learning models for Apple's CoreML framework on iOS and macOS devices.
Many "slow" models are accidentally CPU-bound. Configure via MLModelConfiguration.computeUnits:
| .all | Uses all available compute units including Neural Engine (default, recommended) | | .cpuAndNeuralEngine | CPU + Neural Engine, excludes GPU | | .cpuAndGPU | CPU + GPU, excludes Neural Engine | | .cpuOnly | Forces CPU-only execution (for debugging/consistency) |
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. Source: ckorhonen/claude-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/ckorhonen/claude-skills --skill coreml-optimizerOptimize 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. Source: ckorhonen/claude-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/ckorhonen/claude-skills --skill coreml-optimizer Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/ckorhonen/claude-skills