Intro handbook details scalable Mixture-of-Experts training setup

An introductory technical handbook explains how to train a Mixture-of-Experts (MoE) model at scale, highlighting the transition from dense architectures to sparse models. It covers cluster setup, hardware validation using all-to-all communication benchmarks, Enroot and Pyxis image building, dataset tokenization with FineWev-Edu, and baseline training runs. Open article →