[{"_1":2,"_72":-5,"_73":-5},"loaderData",{"_3":4,"_44":45},"root",{"_5":-5,"_6":-5,"_7":8,"_22":23,"_24":25,"_26":27,"_30":31,"_36":37,"_38":39,"_40":41},"user","shoppingCartId","shoppingCart",{"_9":10,"_11":12,"_13":14,"_15":16,"_17":18,"_19":20,"_21":14},"id","no-cart","count",0,"free",true,"updatedAt","","paymentGateway","STRIPE","cartItems",[],"loading","locale","en","readerTheme","light","constants",{"_28":29},"paypalClientId","AX53Cwz8jR6rVVzzZiZNWWXl0dGagi-GZrjG-S3Ua14E5nrKMn7DxDQ730O4R8LusLPp49ALn6aRVaEy","publishers",{"_32":33,"_34":35},"companies",[],"universities",[],"learnerOrganizations",[],"needsLocaleCookieSync",false,"announcements",{"_42":-5,"_43":-5},"announcement_store","announcement_authors","routes/_store+/_readers+/email_author.$slug/route",{"_46":47,"_71":-5},"book",{"_9":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58},"Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNzcyNDY","title","MLX Swift & Local LLMs. Deep dive into Apple's MLX framework for high-performance machine learning.","state","published","contactAuthorMethod","email","aboutText","

Unlock the full power of Apple Silicon with the definitive guide to MLX Swift and Local LLMs.

The future of Artificial Intelligence is local. In Volume 6 of the Swift & AI Masterclass, author Edgar Milvus takes you deep into the architecture of Apple's MLX framework, a high-performance array library designed for the \"Metal-to-Model\" experience. This isn't just about calling APIs; it's about building custom inference engines and fine-tuning models directly on your Mac, iPhone, and iPad.

What’s inside this volume:

Unified Memory Mastery: Learn to exploit zero-copy data sharing between CPU and GPU for lightning-fast tensor operations.
Local LLM Deployment: Step-by-step guides on porting HuggingFace weights and running models like Llama and Mistral natively in Swift.
Parameter-Efficient Fine-Tuning (LoRA): Teach your models new tricks using user-specific data without the cost of full retraining.
Quantization & Performance: Master 4-bit and 8-bit quantization to run multi-billion parameter models on mobile devices.
Streaming & Agentic Loops: Build responsive SwiftUI chat interfaces and autonomous agents that can call Swift functions as tools.

Bridging the gap between Python-based research and Swift-based production, this book provides the theoretical foundations and the production-ready code needed to build the next generation of privacy-centric, offline-first AI applications. Whether you are an experienced iOS developer or a Machine Learning engineer, this masterclass is your roadmap to AI excellence on Apple platforms.

Note: This book requires a Mac with Apple Silicon for the code examples.

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