Instructions to use BryanW/43.a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BryanW/43.a with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BryanW/43.a", 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:
- a9f4836afdbcfdaf4cc489aaa06f3abc3c56d2d4142ece0d73ad05914fb05bbe
- Size of remote file:
- 16.1 kB
- SHA256:
- 09eb7ff14a692816afd92d45410df9745723fed2ee73c60c943008f86e34b8ad
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