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:
- 5fbcb055762bb8008d07e00b7f2e0833234cf11b2c5af3be5cda4d7dc5b9553d
- Size of remote file:
- 3.44 GB
- SHA256:
- d041bdb06fc3ee4793dd9085a501b5c8337e51aba71446a9abcf59d274d70a9f
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