Instructions to use rohhaiil/SysMLv2-Repair-Qwen2.5-Coder-1.5B-Instruct-Patch-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rohhaiil/SysMLv2-Repair-Qwen2.5-Coder-1.5B-Instruct-Patch-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "rohhaiil/SysMLv2-Repair-Qwen2.5-Coder-1.5B-Instruct-Patch-LoRA") - Notebooks
- Google Colab
- Kaggle
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-1.5B-Instruct. It has been trained using TRL on this dataset. It generates diff patches for repairing the code.
Framework versions
- PEFT 0.18.0
- TRL: 0.26.2
- Transformers: 4.57.3
- Pytorch: 2.2.2
- Datasets: 4.4.2
- Tokenizers: 0.22.2
Citation
GitHub Repository: SysMLv2 Repair with KG-SLMs
@inproceedings{alshami2026sysml,
title={Automated Semantic Fault Localization in SysML v2: A Human-in-the-Loop Framework Using Knowledge-Graph Augmented LLMs},
author={Al-Shami, Haitham and Malik, Rohail and Ala-Laurinaho, Riku and Veps{\"a}l{\"a}inen, Jari and Viitala, Raine},
booktitle={Proceedings of the 36th INCOSE International Symposium},
year={2026},
address={Yokohama, Japan},
month={June},
date={16}
}
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Model tree for rohhaiil/SysMLv2-Repair-Qwen2.5-Coder-1.5B-Instruct-Patch-LoRA
Base model
Qwen/Qwen2.5-1.5B Finetuned
Qwen/Qwen2.5-Coder-1.5B Finetuned
Qwen/Qwen2.5-Coder-1.5B-Instruct