Table of Contents

Fine-Tuning Gemma 4 with QLoRA for Customer Support

Why Not Fine-Tune the Entire Model?

Understanding LoRA

Understanding QLoRA

What We Will Build

Configuring Your Development Environment

Setup and Imports

Supervised Fine-Tuning Gemma 4 on the Bitext Customer Support Dataset

Summary

Large language models such as Gemma 4 are capable of handling a wide range of natural-language tasks out of the box. But when building a specialized application, general-purpose language understanding is only part of the problem.

Consider a customer support assistant for an online store. Customers might ask about orders, refunds, cancellations, invoices, shipping policies, or account-related issues. While Gemma 4 can generate reasonable responses to many of these questions, its pretrained knowledge does not include the specific products, policies, terminology, or communication style of a particular business.

One way to address this is through prompt engineering .…