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SkillsMP는 hbmartin/Foundation-Models-and-Core-AI-and-MLX-skills에서 10개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 10개 중 10개를 표시합니다.
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…
원문 언어: 영어
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…
원문 언어: 영어
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…
원문 언어: 영어
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…
원문 언어: 영어
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…
원문 언어: 영어
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,…
원문 언어: 영어
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…
원문 언어: 영어
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,…
원문 언어: 영어
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…
원문 언어: 영어
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.…
원문 언어: 영어