Instructions to use TencentARC/ColorFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TencentARC/ColorFlow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TencentARC/ColorFlow", 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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@@ -85,14 +85,11 @@ The overview of ColorFlow. This figure presents the three primary components of
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### 📜 Citation
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```
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@
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title={ColorFlow: Retrieval-Augmented Image Sequence Colorization},
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author={
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2412.11815},
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}
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```
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### 📜 Citation
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```
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@article{zhuang2024colorflow,
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title={ColorFlow: Retrieval-Augmented Image Sequence Colorization},
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author={Zhuang, Junhao and Ju, Xuan and Zhang, Zhaoyang and Liu, Yong and Zhang, Shiyi and Yuan, Chun and Shan, Ying},
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journal={arXiv preprint arXiv:2412.11815},
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year={2024}
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}
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```
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