Instructions to use Amazingldl/VisualBox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Amazingldl/VisualBox with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Amazingldl/VisualBox", 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:
- fdb5e7bf1c9d46850813b7f0ff1dd0b4d3987b9dd70e33955b2f5b37779cea09
- Size of remote file:
- 492 MB
- SHA256:
- 3b83ebad89114700a6c70e5bc929b22613fe09e88f279bdd8452e27980e22bc9
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