The Abliterated LLM Handbook

A complete, hands-on guide to running uncensored open-weight LLMs — where you control them. Learn what abliteration actually does to a network's weights, how to read the Gemma 3, Qwen3, Llama 3.1, gpt-oss and GLM variant maze, and how to install, run, tune, serve and build on every major release — ending with a full chapter that walks you through abliterating a model yourself. By the end, you'll be able to: — Run any major abliterated model on your own hardware, from a laptop to a 24GB GPU — Pick the right quantization and model size for your exact VRAM budget, without guesswork — Deploy a production-grade API server (vLLM, llama.cpp, Ollama, Docker) with proper security — Build a working RAG application and a tool-calling agent on top of an uncensored model — Abliterate a model yourself, from scratch, with complete working code 11 chapters · 11 labs · 60+ runnable commands · 5 runtime stacks · 256K max context handled