Training

Instruction Tuning

Instruction tuning fine-tunes models on examples of instructions paired with high-quality responses. This transforms raw language models into helpful assistants. Instruction tuning teaches models to: follow explicit instructions, refuse unsafe requests, and format responses appropriately. High-quality instruction data is more valuable than quantity. Instruction tuning is typically followed by RLHF or DPO for further improvement. Many open models use instruction tuning. It's foundational for making models practical.