---
title: Large language models (LLMs) | Databricks on AWS
source: https://docs.databricks.com/aws/en/machine-learning/ai-runtime/examples/gpu-llms
ingestedAt: "2026-06-18T08:08:38.254Z"
---

Public Preview

AI Runtime for single-node tasks is in [Public Preview](https://docs.databricks.com/aws/en/release-notes/release-types). The distributed training API for multi-GPU workloads remain in [Beta](https://docs.databricks.com/aws/en/release-notes/release-types).

This page provides notebook examples for fine-tuning large language models (LLMs) using AI Runtime. These examples demonstrate various approaches to fine-tuning including parameter-efficient methods like Low-Rank Adaptation (LoRA) and full supervised fine-tuning.

## Video demo[​](#video-demo "Direct link to Video demo")

This video walks through the [Fine-tune Llama-3.2-3B with Unsloth](https://docs.databricks.com/aws/en/machine-learning/ai-runtime/examples/tutorials/sgc-finetune-llama-unsloth) example notebook in detail (12 minutes).
