Chapter 9: Distributed Training and Scaling with Tunix

Fri, 30 Jan 2026 00:00:00 +0000

Chapter 9: Distributed Training and Scaling with Tunix

Welcome back, intrepid Tunix explorer! So far, we’ve mastered the fundamentals of Tunix, understood its core concepts, and even applied it to fine-tune smaller language models. But what happens when our models grow to billions or even trillions of parameters? What happens when our datasets are so massive that a single GPU or even a single machine can’t handle them?

That’s where distributed training comes in! In this chapter, we’re going to dive into the exciting world of scaling our LLM post-training efforts. We’ll learn how Tunix, powered by JAX, allows us to harness the power of multiple devices – whether they’re GPUs or TPUs – to train larger models faster and more efficiently.

Chapter 17: Distributed Training & Scaling Deep Learning

Sat, 17 Jan 2026 00:00:00 +0000

Chapter 17: Distributed Training & Scaling Deep Learning

Welcome back, future AI architect! In our journey so far, we’ve built a strong foundation in deep learning, mastering neural network architectures, understanding training workflows, and optimizing models. We’ve even considered how powerful hardware like GPUs accelerate our tasks. But what happens when your model becomes so massive it won’t fit on a single GPU? Or when your dataset is so enormous that training takes weeks, even on the most powerful single machine?

Distributed Training on AI VOID

Chapter 9: Distributed Training and Scaling with Tunix