Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models
Paper • 2504.11514 • Published
How to use nibauman/RobotxLLM_Qwen7B_SFT with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-7b-instruct-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "nibauman/RobotxLLM_Qwen7B_SFT")This model is a fine-tuned version of unsloth/Qwen2.5-7B-Instruct designed for decision-making and control adaptation in autonomous driving systems. It was developed as part of the RSS 2025 paper Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models.
This model builds on Qwen2.5-7B-Instruct via LoRA based SFT. It is trained on a synthetic dataset obtained from GPT-4o of driving instructions and corresponding robot interactions with it's corresponding low-level MPC controller to adhere to natural language commands.
unsloth/Qwen2.5-7B-Instruct