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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).
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We fine-tune Qwen2.5-1.5B-Instruct to enable **adaptive safety reasoning activation**.
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The model triggers explicit safety reasoning only under jailbreak-like semantics, while avoiding unnecessary safety reasoning on benign or general prompts.
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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 alignment
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- small language models
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- 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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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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