Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. However, to harness their full potential for real-world impact, it's crucial to adapt them effectively. This involves choosing appropriate training and algorithms to enhance model performance on specific tasks. By emphasizing on