Add model card

README.md

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+---
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- alignment
+- evaluation
+- preference-learning
+- ripd
+base_model: sirev/Gemma-2b-Uncensored-v1
+datasets:
+- ZDCSlab/ripd-dataset
+---
+
+# ZDCSlab/ripd-anthropic-saferlhf-gemma-2b-uncensored-v1-biased-bt
+
+This checkpoint is part of the artifact release for  
+**“Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges.”**
+
+It is a policy model trained under a specific rubric condition to study how evaluation-time preference drift propagates into downstream alignment.
+
+---
+
+## Configuration
+
+- **Setting:** anthropic-saferlhf  
+- **Base model:** [Gemma-2b-Uncensored-v1](https://huggingface.co/sirev/Gemma-2b-Uncensored-v1)  
+- **Label condition:** biased  
+- **Training data:** Bench + Target (mixed)  
+- **Objective:** Direct Preference Optimization (DPO)
+
+The `biased` condition corresponds to preference labels generated by an LLM judge under the `biased` rubric variant.
+
+---
+
+## Intended Use
+
+This model is released for research on evaluation-time robustness, preference drift, and alignment propagation.  
+It is not intended for production deployment.
+
+---
+
+## Resources
+
+- 📄 Paper: https://www.arxiv.org/pdf/2602.13576  
+- 💻 Code & Evaluation Pipeline: https://github.com/ZDCSlab/Rubrics-as-an-Attack-Surface  
+- 📊 Dataset: https://huggingface.co/datasets/ZDCSlab/ripd-dataset