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SocraticLM-Qwen-Lora
Aditya-m04/SocraticLM-Qwen-Lora
SocraticLM-Qwen-Lora is a machine learning model from Aditya-m04. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
This repository contains a LoRA adapter fine-tuned on 160k curated pedagogical dialogs designed for step-by-step Socratic teaching, self-explanation, and guided reasoning.
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.safetensors323 MB · 95%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Dec 5, 2025
- Updated
- Dec 5, 2025
- SHA
- eb050dcd
Base models
Model card
From the Hugging Face model README
🧠 SocraticLM-Qwen-LoRA
LoRA-Fine-Tuned Qwen2.5-7B-Instruct for Pedagogy-Optimized Teaching Conversations
This repository contains a LoRA adapter fine-tuned on 160k curated pedagogical dialogs
designed for step-by-step Socratic teaching, self-explanation, and guided reasoning.
The base model remains unchanged:
👉 Qwen/Qwen2.5-7B-Instruct
and this repo stores only the LoRA weights (adapter_model.safetensors).
🚀 How to Use
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = "Qwen/Qwen2.5-7B-Instruct"
adapter = "Aditya-m04/SocraticLM-Qwen-Lora"
tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)
inp = "Explain the Pythagorean theorem to a 10-year-old."
out = model.generate(**tokenizer(inp, return_tensors="pt").to(model.device), max_new_tokens=200)
print(tokenizer.decode(out[0], skip_special_tokens=True))
- Library
- peft
- License
- apache-2.0
- Created
- Dec 5, 2025
- Updated
- Dec 5, 2025