What is Instruction Tuning?
Instruction Tuning — Fine-tuning an AI model specifically to follow user instructions and commands.
Instruction tuning teaches a base model to follow natural language commands. Without it, raw LLMs tend to continue text rather than respond to questions. This is the process that transforms a text-completion model into a useful assistant.
Frequently Asked Questions
What is the difference between instruction tuning and RLHF?
Instruction tuning trains the model to follow commands using supervised examples. RLHF then refines the model based on human preference rankings. They are sequential steps in creating an AI assistant.
Can I instruction-tune an open source model?
Yes. Datasets like FLAN, OpenAssistant, and Dolly are publicly available. Combined with PEFT techniques like LoRA, you can instruction-tune models on a single GPU.
Why do base models need instruction tuning?
Base models are trained to predict the next word in text. Without instruction tuning, asking a question might result in the model generating more questions instead of answering yours.