--- dataset_info: features: - name: are_different dtype: bool - name: best_image_uid dtype: string - name: caption dtype: string - name: created_at dtype: timestamp[ns] - name: has_label dtype: bool - name: image_0_uid dtype: string - name: image_0_url dtype: string - name: image_1_uid dtype: string - name: image_1_url dtype: string - name: jpg_0 dtype: binary - name: jpg_1 dtype: binary - name: label_0 dtype: float64 - name: label_1 dtype: float64 - name: model_0 dtype: string - name: model_1 dtype: string - name: ranking_id dtype: int64 - name: user_id dtype: int64 - name: num_example_per_prompt dtype: int64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 193273338802 num_examples: 583747 - name: validation num_bytes: 5638295249 num_examples: 17439 - name: test num_bytes: 4621428929 num_examples: 14073 - name: validation_unique num_bytes: 178723392 num_examples: 500 - name: test_unique num_bytes: 178099641 num_examples: 500 download_size: 202289408791 dataset_size: 203889886013 --- # Dataset Card for Pick-a-Pic (v1) ## Dataset Description - **Homepage: The web app can be found at [pickapic.io](https://pickapic.io/)** - **Repository: The repository of [PickScore](https://github.com/yuvalkirstain/PickScore)** - **Paper: [Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation](https://arxiv.org/abs/2305.01569).** - **Leaderboard: TODO ** - **Point of Contact: TODO ** ### Dataset Summary The Pick-a-Pic dataset was collected with the [Pick-a-Pic web app](https://pickapic.io/) and contains over half-a-million examples of human preferences over model-generated images. This dataset with URLs instead of the actual images (which makes it much smaller in size) can be found [here](https://huggingface.co/datasets/yuvalkirstain/pickapic_v1_no_images). See the corresponding paper [Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation](https://arxiv.org/abs/2305.01569) for more details. ### Supported Tasks and Leaderboards TODO ### Data Splits The dataset has three main splits: train, validation, validation_unique (with one example per prompt), test, and test_unique. ### Citation Information