How do modern LLMs implement instruction tuning at scale?

Instruction tuning trains models on diverse task instructions to improve generalization.

Instruction tuning uses datasets containing task descriptions and desired outputs. Models are trained to follow natural language instructions rather than task-specific labels. This improves zero-shot generalization and aligns model behavior with user intent.