In this talk, we introduce a streamlined method for training smaller, task-specific models without the need for new data by utilizing foundational models. We'll cover the process of leveraging existing open-source foundational large models to impart knowledge to more compact models tailored for specific tasks. The focus will be on how developers can apply these techniques using open-source tools to enhance their projects.