Quantizing LLMs: Step-by-Step FP16 to GGUF Conversion Guide
The Imperative of Efficient AI: Mastering LLM Quantization In the rapidly evolving landscape of Artificial Intelligence, the democratization of Large Language Models (LLMs) hinges on a critical technological pivot: Quantization. As models scale to hundreds of billions of parameters, the computational cost of inference in standard Floating Point 16 (FP16) precision becomes prohibitive for