Applying open-source LLMs in Social & Behaviour Sciences



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Further and more detailed information, including the schedule, can be found in the current course tables in the syllabus of the respective course, if the course is offered in the next sessions. The following text serves as information on what can be expected in terms of content in the course.

The course introduces the use of open-source large language models (LLMs) from the Hugging Face ecosystem for research in the behavioral and social sciences. In short lectures, participants will learn about key concepts (e.g., embeddings, causal attention, feature extraction, classification, prediction, fine-tuning, and token generation) and practical examples from social and behavioral science. In hands-on exercises, participants will apply language models to answer research questions from psychology, political science, decision-making research, and other fields. During and after the course, participants will engage in a personal research project applying LLMs to a personal research question. Two lecturers will hold this course, implying a high level of support during the exercises and research project design.

LLMs (think ChatGPT) are incredibly useful tools for research in the social and behavioral sciences. In this course, you will (1) learn about the fundamental principles of LLMs, (2) learn how to employ open-source LLMs using the Hugging Face ecosystem, (3) learn about the rich opportunities that LLMs offer for behavioral and social science research, and (4) gain experience in applying LLMs to answer personal research questions.