Learn how to easily finetune FunctionGemma, a small language model, using the JAX-based Tunix library on Google TPUs for fast and cost-effective agent development.- Google Developers Blog

This post details the process of fine-tuning the FunctionGemma language model using the JAX-based Tunix library on Google TPUs. It provides code examples for loading models and datasets, setting up JAX sharding, applying LoRA adapters with Qwix, defining a custom dataset for completion-only loss, and initiating the training process. The post highlights the efficiency of Tunix in achieving high TPU utilization and significant accuracy improvements after one epoch, and demonstrates merging LoRA adapters for on-device deployment with LiteRT.