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:
- 339f6388c5b084bb76b76f228ec55301425963dcc3a59669d97c796931a3a84b
- Size of remote file:
- 16.1 kB
- SHA256:
- 89eb85e93c098918435bad50eac188f9c8eefc1faa8baac2290e75c36d274559
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