Own your AI: Learn how to fine-tune Gemma 3 270M and run it on-device- Google Developers Blog

This post details the process of fine-tuning Gemma 3 270M for a specific task (text-to-emoji translation) using QLoRA for parameter-efficient fine-tuning. It then describes quantizing the model to under 300MB for on-device deployment and running it client-side in a web app using MediaPipe or Transformers.js, leveraging WebGPU for local computation. This demonstrates a practical workflow for creating and deploying specialized, on-device AI models.