Llama-3.1-8B-SafeSci-LoRA

yyy127/Llama-3.1-8B-SafeSci-LoRA

Llama-3.1-8B-SafeSci-LoRA is a machine learning model from yyy127. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

This is the LoRA-finetuned version of the original model on SafeSciTrain to enhance the safety. This model support standard (text) behaviors and contextual behaviors.

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At a glance

Model type: llama
Access: Public
Created: Feb 25, 2026
Updated: Mar 4, 2026
SHA: 3a3112f2

Model card

From the Hugging Face model README

📝 Overview:

This is the LoRA-finetuned version of the original model on SafeSciTrain to enhance the safety. This model support standard (text) behaviors and contextual behaviors.

📚 To test the model, please use vllm>=0.11.1. Code to use the model can be found in our github 💻

💬📊 Performances

Performance on Safety Knowledge questions. We present the accuracy of seven fields and their average.

	Chem.	Bio.	Med.	Mat.	Eng.	Phy.	Psy.	Avg.
Qwen3-8B	0.52	0.56	0.56	0.68	0.68	0.67	0.68	0.59
+ LoRA	0.77	0.42	0.84	0.77	0.63	0.53	0.69	0.70
Qwen3-14B	0.56	0.65	0.53	0.75	0.66	0.59	0.66	0.60
+ LoRA	0.84	0.45	0.88	0.86	0.70	0.55	0.71	0.75
Llama3.1-8B	0.46	0.75	0.57	0.66	0.53	0.56	0.62	0.57
+ LoRA	0.79	0.42	0.81	0.72	0.53	0.56	0.68	0.66

Safety rate on Safety Risk questions. We present the rejection rate of seven fields and their average.

	Chem.	Bio.	Med.	Mat.	Eng.	Phy.	Psy.	Avg.
Qwen3-8B	0.37	0.41	0.21	0.52	0.16	0.23	0.14	0.31
+ LoRA	0.83	0.95	0.94	0.85	0.19	0.28	0.08	0.64
Qwen3-14B	0.31	0.37	0.15	0.39	0.14	0.16	0.11	0.26
+ LoRA	0.76	0.90	0.53	0.94	0.26	0.53	0.14	0.60
Llama3.1-8B	0.49	0.55	0.69	0.87	0.27	0.33	0.20	0.41
+ LoRA	0.94	0.86	0.97	0.99	0.32	0.29	0.21	0.58

📖 Citation:

@misc{zhu2026safescisafetyevaluationlarge,
      title={SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond}, 
      author={Xiangyang Zhu and Yuan Tian and Qi Jia and Kaiwei Zhang and Zicheng Zhang and Chunyi Li and Kaiyuan Ji and Dongrui Liu and Zijian Chen and Lu Sun and Renrui Zhang and Yan Teng and Jing Shao and Wei Sun and Xia Hu and Yu Qiao and Guangtao Zhai},
      year={2026},
      eprint={2603.01589},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2603.01589}, 
}

Type: llama
Created: Feb 25, 2026
Updated: Mar 4, 2026