Fine-tuning

Fine-tuning is the process of adjusting a pre-trained, general-purpose model on a smaller, specialized dataset so that it can better handle a specific task, domain, or communication style. It is significantly faster and cheaper than training a model from scratch, because the model has already acquired basic linguistic and knowledge patterns, and fine-tuning simply adapts them to a specific use case, such as legal terminology or the tone of a particular brand.