Load Core ML models and run on-device predictions in Swift iOS apps.
npx skills add https://github.com/onymchat/onym-ios --skill coreml-onymchat
Please help me install this Agent Skill. Skill: coreml Source: https://github.com/onymchat/onym-ios/tree/main/.claude/skills/coreml Command: npx skills add https://github.com/onymchat/onym-ios --skill coreml-onymchat
This skill streamlines loading Core ML models and running predictions in Swift-based iOS apps, handling model configuration, deployment, and performance profiling on-device.
Load an MLModel and run a swift-based on-device prediction using the provided patterns.
High-intent search queries and answers about installing and using this skill.
Configure Core ML compute units in Swift by managing MLModelConfiguration to target the CPU, GPU, or Neural Engine. This controls hardware allocation and optimizes on-device inference performance across app sessions.
Vision framework integration with Core ML handles image preprocessing and prediction workflows in Swift. It manages image inputs and batch predictions by passing processed data directly to your MLModel.
Profile Core ML on-device performance by evaluating compute units and prediction latency during model deployment. This identifies bottlenecks across multi-model pipelines and optimizes bundle versus on-demand strategies.
Manage multi-model pipelines and MLMultiArray workflows on iOS by chaining Core ML models and handling multi-dimensional data. This supports complex on-device execution and batch prediction strategies.
inehemiasmConfigure Xcode projects by adding Swift Package dependencies and linking resources.
pradeepmouliConvert PyTorch models to CoreML and optimize for iOS/macOS deployment.
DFly7Integrate Core ML models into iOS apps for on-device inference.
FelixRauchIntegrates Core ML models into iOS apps with Swift APIs and MLModelConfiguration.
