Menu
SkillsMP has collected 10 skills from hbmartin/Foundation-Models-and-Core-AI-and-MLX-skills. Open a skill to review its source and details.
Showing 10 of 10 collected skills.
Measure and regression-test on-device model output with Apple's Evaluations framework: eval harnesses, prompt hill-climbing, model-as-judge graders and alignment, synthetic or adversarial data, and tool-trajectory scoring; also use DNIKit to audit datasets…
Migrate a shipping Apple AI app or model pipeline from the 26 SDK generation to 27: changed APIs, the Foundation Models Adapter sunset, LanguageModelError taxonomy changes, dual-SDK builds, Core ML-to-Core AI decisions, Metal toolchain requirements, and asset…
Ship and operate on-device AI models in released Apple apps: distribution outside the app binary, background asset packs and updates, download and disk budgets, memory pressure and jetsam, thermal throttling, and honest inference benchmarks. Use when choosing…
Expose app content and actions to Siri and Apple Intelligence with App Intents, assistant schema domains, IntentParameter.valueState, AppEntity, IndexedEntity and Spotlight indexing, on-screen awareness, FileEntityIdentifier and FileRepresentation, display…
Build, convert, optimize, and debug Core AI 27 neural models using AIModel, NDArray, bundles, engines, guided decoding, specialization, caching, AOT compilation, coreai-torch conversion, custom Metal ops, quantization, palettization, pruning, and ANE/GPU…
Build and debug apps using Apple's Foundation Models framework: LanguageModelSession, @Generable, @Guide, streaming, tools, the Instructions-versus-Prompt trust boundary, context and KV cache, DynamicProfile, custom LanguageModel backends, Playground,…
Write and debug hand-built on-device ML kernels with Metal TensorOps and Metal Performance Primitives: MPP and MTLTensor APIs, quantized or multiplane operands, cooperative tensors, threadgroup and memory layout, and flash attention. Use when implementing an…
Build and debug MLX in Python or Swift: mx.array and lazy evaluation, unified memory, mx.compile and transforms, custom kernels, quantization, mlx-lm generation and prompt caching, serving, distributed inference, fine-tuning, model ports, mlx-swift-lm apps,…
Choose among Apple Foundation Models, Core AI, MLX, Metal, or Core ML for on-device inference, and apply OS, SDK, hardware, and availability gates across Apple platforms. Use when selecting a stack; writing @available or SystemLanguageModel.availability…
Build and debug speech-to-text with Apple's Speech framework: SpeechAnalyzer, SpeechTranscriber, DictationTranscriber, AssetInventory installation, custom vocabulary, live or file transcription, AnalyzerInputConverter, and volatile versus finalized results.…