Comparison
Fine-tuning vs Instruction Tuning
Fine-tuning and Instruction Tuning are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Fine-tuning
After you've exhausted prompting and retrieval, and you have a few hundred to thousands of clean labeled examples.
Fine-tuning Llama 3 on medical Q&A for a clinical assistant.
When you would reach for Instruction Tuning
Instruction Tuning comes up when the question is fundamentally about training.
FLAN tuning Google's T5 to follow instructions.
Frequently asked
What is the difference between Fine-tuning and Instruction Tuning?
Fine-tuning: Fine-tuning continues training a pretrained model on a smaller, task-specific dataset, adjusting its weights to specialize behavior or knowledge. Instruction Tuning: Instruction tuning is fine-tuning on examples of (instruction, desired response) pairs so a base model learns to follow natural-language directions.
When should I use Fine-tuning vs Instruction Tuning?
After you've exhausted prompting and retrieval, and you have a few hundred to thousands of clean labeled examples. Instruction Tuning applies when you are focused on training.
Are Fine-tuning and Instruction Tuning the same thing?
No. Fine-tuning is training; Instruction Tuning is training. They are related but address different parts of the AI stack.