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@@ -17,6 +17,8 @@ tags:
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  - mistral
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  - salad-bench
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  - evluation
 
 
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  ---
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  # MD-Judge for Salad-Bench
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  MD-Judge is a LLM-based safetyguard, fine-tund on top of [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-v0.1). MD-Judge serves as a classifier to evaluate the safety of QA pairs.
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- MD-Judge was born to study the safety of different LLMs serving as an general evaluation tool, which is proposed under the [SALAD-Bench paper](https://arxiv.org/abs/2402.02416)
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-
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- - **Developed by:** The SALAD-Bench Team
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- - **Model type:** An auto-regressive language model based on the transformer architecture.
 
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  ## Model Sources
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- - **Repository:** [SALAD-Bench Github](https://github.com/OpenSafetyLab/SALAD-BENCH)
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- - **Paper:** [SALAD-BENCH](https://arxiv.org/abs/2402.02416)
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-
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  ## Model Performance
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  Compare our MD-Judge model with other methods on different public safety testsets using QA format. All the model-based methods are evaluated using the same safety proxy template.
@@ -122,5 +124,4 @@ Please refer to our [Github](https://github.com/OpenSafetyLab/SALAD-BENCH) for m
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  archivePrefix={arXiv},
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  primaryClass={cs.CL}
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  }
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- ```
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-
 
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  - mistral
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  - salad-bench
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  - evluation
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+ - judge
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+ pipeline_tag: text-generation
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  ---
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  # MD-Judge for Salad-Bench
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  MD-Judge is a LLM-based safetyguard, fine-tund on top of [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-v0.1). MD-Judge serves as a classifier to evaluate the safety of QA pairs.
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+ MD-Judge was born to study the safety of different LLMs serving as an general evaluation tool, which is proposed under the 🥗SALAD-Bench. You can check the following source for more information:
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+ - [**Paper**](https://arxiv.org/abs/2402.02416)
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+ - [**Code**](https://github.com/OpenSafetyLab/SALAD-BENCH)
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+ - [**Data**](https://huggingface.co/datasets/OpenSafetyLab/Salad-Data)
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+ - [**Project Page**](https://adwardlee.github.io/salad_bench/)
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  ## Model Sources
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+ - **Repository:** [SALAD-Bench Github]()
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+ - **Paper:** [SALAD-BENCH]()
 
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  ## Model Performance
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  Compare our MD-Judge model with other methods on different public safety testsets using QA format. All the model-based methods are evaluated using the same safety proxy template.
 
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  archivePrefix={arXiv},
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  primaryClass={cs.CL}
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  }
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+ ```