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:
- 5ce257f2d345d8c9196218c0ba8fdfde5ca79e5360f8bd85e04d1f797fd93edc
- Size of remote file:
- 2.89 GB
- SHA256:
- 74414eae61d7dfc2ca220632232c126483bd96742a5b6457417dfc5bca9b0bf6
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