PolicyShiftGuard 7B RP SFT

--- base_model: Qwen/Qwen2.5-VL-7B-Instruct datasets: - PolicyShiftBench/PolicyShiftBench library_name: transformers license: apache-2.0 pipeline_tag: image-text-to-text tags: - vision-language - safety - guardrail - policy-conditioned - qwen2.5-vl - policyshiftguard --- # PolicyShiftGuard-7B-RP-SFT [\ud83d\udcc3 Paper](https://arxiv.org/abs/2607.05910) | [\ud83c\udf10 Project Page](https://policyshiftguard.github.io/) | [\ud83d\udcbb GitHub](https://github.com/ssmisya/PolicyShiftGuard) This repository releases the **Stage-1 Randomized Policy SFT (RP-SFT)** checkpoint for the 7B PolicyShiftGuard model. RP-SFT is the first training stage in PolicyShiftGuard. It trains a Qwen2.5-VL guardrail model to read policy bundles under randomized policy identifiers and randomized policy ordering. This checkpoint is provided for reproducibility and ablation use. The final public model after the second-stage adaptation is available at [`PolicyShiftGuard/PolicyShiftGuard-7B`](https://huggingface.co/PolicyShiftGuard/PolicyShiftGuard-7B). ## Intended Use Use this checkpoint when you want to reproduce the two-stage training pipeline or compare Stage-1 RP-SFT against the final BP-Adapt model. For standard evaluation or deployment, use the final model instead: - [`PolicyShiftGuard/PolicyShiftGuard-7B`](https://huggingface.co/PolicyShiftGuard/PolicyShiftGuard-7B) ## Dataset The model is trained with PolicyShiftBench supervision: - [`PolicyShiftBench/PolicyShiftBench`](https://huggingface.co/datasets/PolicyShiftBench/PolicyShiftBench) ## Notes - This is an intermediate checkpoint, not the final model reported as the main PolicyShiftGuard model. - This checkpoint corresponds to the randomized-policy no-think Stage-1 SFT setting. - Training-state files such as optimizer states are intentionally not included. ## Citation If you find this work helpful, please cite the paper: ```bibtex @article{song2026policyshiftguard, title = {PolicyShiftGuard: Benchmarking and Improving Policy-Adaptive Image Guardrails}, author = {Song, Mingyang and Xu, Luxin and Sun, Haoyu and Pan, Minzhou and Cheng, Yu and Li, Bo}, journal = {arXiv preprint arXiv:2607.05910}, year = {2026} } ```

--- license: apache-2.0 base_model: Qwen/Qwen2.5-VL-7B-Instruct library_name: transformers pipeline_tag: image-text-to-text tags: - vision-language - safety - guardrail - policy-conditioned - qwen2.5-vl - policyshiftguard datasets: - PolicyShiftBench/PolicyShiftBench --- # PolicyShiftGuard-7B-RP-SFT This repository releases the **Stage-1 Randomized Policy SFT (RP-SFT)** checkpoint for the 7B PolicyShiftGuard model. RP-SFT is the first training stage in PolicyShiftGuard. It trains a Qwen2.5-VL guardrail model to read policy bundles under randomized policy identifiers and randomized policy ordering. This checkpoint is provided for reproducibility and ablation use. The final public model after the second-stage adaptation is available at [`PolicyShiftGuard/PolicyShiftGuard-7B`](https://huggingface.co/PolicyShiftGuard/PolicyShiftGuard-7B). ## Intended Use Use this checkpoint when you want to reproduce the two-stage training pipeline or compare Stage-1 RP-SFT against the final BP-Adapt model. For standard evaluation or deployment, use the final model instead: - [`PolicyShiftGuard/PolicyShiftGuard-7B`](https://huggingface.co/PolicyShiftGuard/PolicyShiftGuard-7B) ## Dataset The model is trained with PolicyShiftBench supervision: - [`PolicyShiftBench/PolicyShiftBench`](https://huggingface.co/datasets/PolicyShiftBench/PolicyShiftBench) ## Notes - This is an intermediate checkpoint, not the final model reported as the main PolicyShiftGuard model. - This checkpoint corresponds to the randomized-policy no-think Stage-1 SFT setting. - Training-state files such as optimizer states are intentionally not included.

Source context: 51 downloads · 0 likes · Pipeline image-text-to-text · Library transformers · Repo PolicyShiftGuard/PolicyShiftGuard-7B-RP-SFT