Instructions to use Zilun/GeoRSSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Zilun/GeoRSSD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Zilun/GeoRSSD", 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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# GeoRSSD
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* Stable Diffusion fine-tuned by RS5M with 1%(1p) data and 20% data(20p)
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**Please refer to [this repo](https://github.com/ShivamShrirao/diffusers/tree/main/examples/dreambooth) for using checkpoint to inference.**
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# GeoRSSD
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* Stable Diffusion (2.1) fine-tuned by RS5M with 1%(1p) data and 20% data(20p)
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**Please refer to [this repo](https://github.com/ShivamShrirao/diffusers/tree/main/examples/dreambooth) for using checkpoint to inference.**
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