Instruction Tuning

Instruction tuning is one of the key steps that transforms large language models from general text generators into task-following systems. The model learns to solve diverse tasks through instructions written in natural language. This makes a major difference in classification, summarization, information extraction, and agent-oriented use cases. It is one of the most critical training stages behind modern LLM behavior quality.