Adapting Large Language Models to Applications

This chapter explores the adaptation of pretrained Large Language Models (LLMs) for various downstream applications. It discusses advanced techniques beyond traditional fine-tuning, including prompt optimization, pre-prompting, implicit prompting, and model coordination through actor agents. The author provides an overview of the strengths and weaknesses of each method, enabling users to select the most suitable approach for their specific needs in leveraging LLMs effectively.