title: Fine-Tuning description: Learn how to fine-tune pre-trained models for specific tasks using various toolkits and datasets. keywords:

• fine-tuning
• pre-trained models
• chatbots
• dataset preparation

Welcome to the chapter on Fine-Tuning! Here, you'll dive into the exciting world of enhancing pre-trained AI models with your own data. Imagine taking a powerful model that understands general language and teaching it specific tasks like generating code snippets or answering questions about a particular framework.

In this part, we’ll explore how to fine-tune these models using different toolkits such as Hugging Face Autotrain, MLX for Apple hardware, and Llama Fine-Tuning. We'll also discuss the importance of having the right dataset—whether it's chat conversations or question-answer pairs—and how to prepare your data in formats like JSONL or CSV.

You’ll learn about special tokens that help models understand different parts of a conversation and ensure your data is correctly formatted for fine-tuning. Plus, we’ll walk you through the process of splitting your dataset into training and validation sets, downloading model weights, and running the actual fine-tuning process.

Once your model is ready, find out how to deploy it using services like Cloudflare or Ollama, and even optimize its performance with techniques like quantization. This chapter will equip you with all the tools and knowledge needed to create a custom AI solution tailored to your needs!

Ready to make your pre-trained models smarter? Let's get started!