Fine-Tuning LLMs: Exploring Supervised vs. Unsupervised Methods with Real-World Examples

Fine-tuning transforms pre-trained models into specialized ones by training them on domain-specific datasets, enhancing their performance in specific tasks. This can be achieved through supervised or unsupervised methods. Supervised fine-tuning uses labeled data to align models with particular tasks, while unsupervised Show more