Build a Large Language Model (From Scratch)

7 Fine-tuning to follow instructions

This chapter covers

• The instruction fine-tuning process of LLMs
• Preparing a dataset for supervised instruction fine-tuning
• Organizing instruction data in training batches
• Loading a pretrained LLM and fine-tuning it to follow human instructions
• Extracting LLM-generated instruction responses for evaluation
• Evaluating an instruction-fine-tuned LLM

Previously, we implemented the LLM architecture, carried out pretraining, and imported pretrained weights from external sources into our model. Then, we focused on fine-tuning our LLM for a specific classification task: distinguishing between spam and non-spam text messages. Now we’ll implement the process for fine-tuning an LLM to follow human instructions, ...