In the span of a few months, with a small team of researchers and engineers, we trained a 70B parameter model from scratch on our own infrastructure that outperformed zero-shot GPT-4o on reasoning-related tasks. Using our cluster for high performance training meant that every component — InfiniBand, Ethernet, GPUs, and the nodes themselves — had to work perfectly. If even a single one of the over 12,000 connections was a little flaky, it could slow down the entire training run.

We're sharing open-source scripts and an end-to-end guide for infrastructure set-up that details the process of making everything work perfectly, and ensuring that it stays that way.

This is one of a three-part toolkit on training a 70b model from scratch. The other two sections focus on evaluations and CARBS, our hyperparameter optimizer; you can find them here: https://imbue.com/research/70b-intro/

Thoughts and questions welcome! :)