
Fine-tuning AI models, especially large language models (LLMs), is a crucial process that allows these models to excel at specific tasks while leveraging their foundational knowledge. This method can be compared to a landscape painter who learns to paint portraits, where the foundational skills remain but are adapted to new specialized tasks. The successful outcome of fine-tuning depends significantly on