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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-oriented research on:
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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!🤗