Instructions to use jsoncx/Boogu-Image-0.1-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jsoncx/Boogu-Image-0.1-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jsoncx/Boogu-Image-0.1-Base", torch_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
- Xet hash:
- 450294db5ff8666e3e43e46ef34ddffdc6fe29cda16ea3f8501692d3adf0c8af
- Size of remote file:
- 10.7 MB
- SHA256:
- 44552037680872b0eb1800050be92a3e7b85a19066d060198468a6ec0c70ca27
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