38 lines
1.5 KiB
Markdown
38 lines
1.5 KiB
Markdown
---
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license: apache-2.0
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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tags:
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- safety
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- alignment
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---
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# Qwen2.5-1.5B-Instruct-EASE
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This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the [EASE-SafetyReasoning](https://huggingface.co/datasets/HaonanShi/EASE-STAR41K-SafetyReasoning-10K) dataset.
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## Model description
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This is the safety reasoning aligned version model under the framework,[**EASE**](https://arxiv.org/pdf/2511.06512). We fine-tune Qwen2.5-1.5B-Instruct to enable **adaptive safety reasoning activation**. The model triggers explicit safety reasoning only under jailbreak-like semantics, while avoiding unnecessary safety reasoning on benign or general prompts. This design aims to maintain the model’s general task effectiveness and efficiency, while improving robustness against jailbreak attacks.
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## Intended use
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Safety-oriented research on:(1)Safety alignment, (2)Small language models and (3)Jailbreak robustness
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## Citation
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If our model could help you, please cite our paper, thanks!🤗
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**EASE: Practical and Efficient Safety Alignment for Small Language Models(AAAI26)(oral)**
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https://arxiv.org/pdf/2511.06512
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```bibtex
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@inproceedings{shi2026ease,
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title={Ease: Practical and efficient safety alignment for small language models},
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author={Shi, Haonan and Wang, Guoli and Ouyang, Tu and Wang, An},
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booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
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volume={40},
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number={44},
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pages={37923--37931},
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year={2026}
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}
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```
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