Finetuning of Large Language Models (LLM)


LLM finetuning refers to the process of adapting a pre-trained LLMs for specific tasks or domains through further training with data-specific material. The term “finetuning” suggests that the model is already developed a general ability to understand language (through the initial training on a large and diverse dataset), and now it is being finetuned to a narrower domain or specific tasks. Common use cases include for example generating SQL queries or summarizing and reproducing questions and answers (Q&A) based on existing text which however were not used for the original LLM training.

Tasks: In the thesis, the following questions will be examined in more detail:

Contact person: Odej Kao (

Start: immediately