This model is a 7-billion parameter causal transformer fine-tuned from Qwen/Qwen2.5-7B-Instruct using Direct Preference Optimization (DPO) and Low-Rank Adaptation (LoRA). It has been aligned to generate multi-turn Socratic dialogues rather than direct factual answers, explicitly designed to foster higher-order thinking in K-12 learners.
1from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
2
3tokenizer = AutoTokenizer.from_pretrained("mudit23/Socratic-Qwen2.5-7B-v2")
4model = AutoModelForCausalLM.from_pretrained("mudit23/Socratic-Qwen2.5-7B-v2")
5generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
6
7prompt = "Teacher: What do you think causes wind to blow?"
8print(generator(prompt, max_new_tokens=100)[0]["generated_text"])
BibTeX:
@misc{jain2025socraticdpo,
title={Enhancing K-12 Critical Thinking through a DPO-Fine-Tuned Socratic Multi-Agent AI Tutor},
author={Jain, Mudit},
year={2025},
howpublished={\url{
https://huggingface.com/mudit23/Socratic-Qwen2.5-7B-v2}}
}