BitNet.cpp - CPU Inference Framework for 1-bit Large Language Models

Learn how to implement and optimize BitNet CPP, the official inference framework for 1-bit Large Language Models (LLMs), in this 52-minute technical tutorial. Explore the implementation of optimized kernels that enable fast and lossless inference of 1.58-bit models on CPU, capable of handling models up to 100 billion parameters. Dive into practical examples using the provided notebook to understand the quantization techniques and framework architecture that make efficient CPU-based inference possible for BitNet models like BitNet b1.58. Master the fundamentals of model optimization and deployment while working with this cutting-edge framework designed for resource-efficient machine learning operations.