Duplicate from Visualignment/CoProv2-SD15

Co-authored-by: I Chieh Chen <CceJJ@users.noreply.huggingface.co>

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README.md

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+---
+license: mit
+task_categories:
+- text-to-image
+tags:
+- safety
+- alignment
+- dpo
+- direct-preference-optimization
+- t2i
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: jpg_0
+    dtype: string
+  - name: jpg_1
+    dtype: string
+  - name: label_0
+    dtype: int64
+  - name: caption
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 3636505691.38
+    num_examples: 31380
+  download_size: 4020960757
+  dataset_size: 3636505691.38
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---
+
+This repository contains **CoProV2**, a synthetically generated dataset of harmful and safe image-text pairs. It was introduced in the paper [AlignGuard: Scalable Safety Alignment for Text-to-Image Generation](https://huggingface.co/papers/2412.10493).
+
+**CoProV2** is specifically designed to enable the application of Direct Preference Optimization (DPO) for safety purposes in Text-to-Image (T2I) models. It facilitates the training of "safety experts" to guide the generative process away from specific safety-related concepts, enabling scalable safety alignment.
+
+For more details, please refer to:
+
+*   **Paper:** [AlignGuard: Scalable Safety Alignment for Text-to-Image Generation](https://huggingface.co/papers/2412.10493)
+*   **Project Page:** [https://alignguard.github.io/](https://alignguard.github.io/)
+*   **Code:** [https://github.com/Visualignment/SafetyDPO](https://github.com/Visualignment/SafetyDPO)

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