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---
library_name: diffusers
license: openrail++
language:
- en
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This model is a fine-tuned SDXL1.0 model. UNet of the model is fine-tuned on the [OpenCOLE1.0 dataset](naoto0804/opencole) to generate images that looks like graphic design but without texts.
## Model Details
### Model Description
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This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
- **Language(s) (NLP):** English
<!-- **License:** Apache-2.0 -->
- **Finetuned from model:** [SDXL1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0).
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### Model Sources [optional]
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- **Repository:** [CyberAgentAILab/OpenCOLE](https://github.com/CyberAgentAILab/OpenCOLE)
- **Paper:** [OpenCOLE: Towards Reproducible Automatic Graphic Design Generation]()
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## Uses
Please refer to [OpenCOLE](https://github.com/CyberAgentAILab/OpenCOLE).
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<!-- ## Bias, Risks, and Limitations -->
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## How to Get Started with the Model
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## Training Details
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### Training Procedure
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<!-- ## Evaluation -->
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<!-- ## Environmental Impact -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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## Technical Specifications
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## Citation
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
<!--**BibTeX:** -->
```
@inproceedings{inoue2024opencole,
title={{OpenCOLE: Towards Reproducible Automatic Graphic Design Generation}},
author={Naoto Inoue and Kento Masui and Wataru Shimoda and Kota Yamaguchi},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
year={2024},
}
```
<!--**APA:** -->
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<!--## Glossary [optional] -->
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## Model Card Contact
[Naoto Inoue](https://github.com/naoto0804)