Using Large Language Models (LLMs) in education presents unique challenges. Typically, LLMs are designed to provide direct answers to questions, which can hinder students’ critical thinking and self-discovery skills. To address this, we focus on fine-tuning LLMs to facilitate Socratic interactions. Instead of giving straightforward answers, these models guide students to explore and find the answers themselves. We achieve this through Direct Preference Optimization (DPO). We test our approach with diverse datasets, including various educational materials and Socratic dialogues. Using advanced models like GPT-4o for evaluation, our results show that DPO successfully fine-tunes LLMs for Socratic dialogue, enhancing their educational value. And you can also run it with Ollama: eurecom-ds/phi-3-mini-4k-socratic! Or, you can learn more about our project at Fine Tuning a Large Language Model for Socratic Interactions, and read our paper
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: eurecom-ds
Теги: phi3, conversational, custom_code, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 38
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
