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pickapic_v1 / README.md
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---
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