---
license: apache-2.0
language:
- ja
- en
pipeline_tag: text-to-image
library_name: diffusers
tags:
- art
datasets:
- common-canvas/commoncatalog-cc-by
- madebyollin/megalith-10m
- madebyollin/soa-full
- alfredplpl/artbench-pd-256x256
---

# Model Card for CommonArt

This is a text-to-image model learning from CC-BY-4.0, CC-0 or CC-0 like images.

## Model Details

### Model Description

At AI Picasso, we develop AI technology through active dialogue with creators, aiming for mutual understanding and cooperation. 
We strive to solve challenges faced by creators and grow together. 
One of these challenges is that some creators and fans want to use image generation but can't, likely due to the lack of permission to use certain images for training.
To address this issue, we have developed CommonArt β. As it's still in beta, its capabilities are limited. 
However, its structure is expected to be the same as the final version.

#### Features of CommonArt β

- Principally uses images with obtained learning permissions
- Understands both Japanese and English text inputs directly
- Minimizes the risk of exact reproduction of training images
- Utilizes cutting-edge technology for high quality and efficiency

### Misc.

- **Developed by:** alfredplpl
- **Funded by:** AI Picasso, Inc.
- **Shared by:** AI Picasso, Inc.
- **Model type:** Diffusion Transformer based architecture
- **Language(s) (NLP):** Japanese, English
- **License:** Apache-2.0

### Model Sources

- **Repository:** [Github](https://github.com/PixArt-alpha/PixArt-sigma)
- **Paper :** [PIXART-δ](https://arxiv.org/abs/2401.05252)

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

[More Information Needed]

### Out-of-Scope Use

- Generate misinfomation such as DeepFake.

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data
We used these dataset to train the diffusion transformer:

- [CommonCatalog-cc-by](https://huggingface.co/datasets/common-canvas/commoncatalog-cc-by)
- [Megalith-10M](https://huggingface.co/datasets/madebyollin/megalith-10m)
- [Smithonian Open Access](https://huggingface.co/datasets/madebyollin/soa-full)
- [ArtBench (CC-0 only) ](https://huggingface.co/datasets/alfredplpl/artbench-pd-256x256)


## Environmental Impact

- **Hardware Type:** NVIDIA L4
- **Hours used:** 20000
- **Cloud Provider:** Google Cloud
- **Compute Region:** Japan
- **Carbon Emitted:** free

## Technical Specifications

### Model Architecture and Objective

[Pixart-Σ based architecture](https://github.com/PixArt-alpha/PixArt-sigma)

### Compute Infrastructure

Google Cloud (Tokyo Region).

#### Hardware

We used NVIDIA L4x8 instance 4 nodes. (Total: L4x32)

#### Software

[Pixart-Σ based code](https://github.com/PixArt-alpha/PixArt-sigma)

## Model Card Contact

[AI Picasso, Inc.](support@aipicasso.app)