Overview

Master Local LLM Deployment and OptimizationStop relying on expensive APIs and take control of your AI infrastructure. The Local LLM Handbook is the definitive technical guide for engineers ready to deploy powerful large language models on their own hardware. Whether you are building private AI agents or optimizing inference for production, this book provides a deep dive into the two most popular backends today: Ollama and Llama.cpp. Architecture Comparison: Understand the trade-offs between Ollama's ease of use and Llama.cpp's granular control. Quantization Demystified: Learn how GGUF works and how to balance speed vs. perplexity. Hardware Optimization: Configure your RAM, VRAM, and CPU for maximum tokens per second. Deployment Patterns: Setting up REST APIs, integration with LangChain, and containerization. Security and Privacy: Techniques for air-gapped AI and data sovereignty. From beginners looking to run their first Llama 3 instance to senior engineers architecting self-hosted RAG systems, this handbook bridges the gap between research and implementation. Take back your data and reduce your cloud costs today.

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