Instructions to use ImagenHub/DreamBooth-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ImagenHub/DreamBooth-Models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ImagenHub/DreamBooth-Models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -6,7 +6,7 @@ Please kindly cite our paper if you use our code, data, models or results:
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```bibtex
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@article{ku2023imagenhub,
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title={ImagenHub: Standardizing the evaluation of conditional image generation models},
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author={Max Ku
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journal={arXiv preprint arXiv:2310.01596},
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year={2023}
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}
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```bibtex
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@article{ku2023imagenhub,
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title={ImagenHub: Standardizing the evaluation of conditional image generation models},
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author={Max Ku and Tianle Li and Kai Zhang and Yujie Lu and Xingyu Fu and Wenwen Zhuang and Wenhu Chen},
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journal={arXiv preprint arXiv:2310.01596},
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year={2023}
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}
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