# LLM Fine-Tuning

> SFT, LoRA, QLoRA, DPO, and GRPO — when and how to fine-tune large language models responsibly.

![Status: complete](https://img.shields.io/badge/status-complete-brightgreen)

Open [`12-llm-finetuning.ipynb`](./12-llm-finetuning.ipynb) for learning objectives, prerequisites, and recommended reading order.

## Topics Covered

- Supervised fine-tuning and dataset preparation
- LoRA and QLoRA for memory-efficient training
- DPO and GRPO alignment techniques
- Evaluation, quantisation (GPTQ/AWQ), and deployment

## Prerequisites

[11-prompt-engineering/README.md](../11-prompt-engineering/README.md) · [09-mlops/README.md](../09-mlops/README.md)

## What Comes Next

[13-multimodal/README.md](../13-multimodal/README.md) or [14-local-llms/README.md](../14-local-llms/README.md)
