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:
- a7f9ce917b34a10f6ad4a4758e7ac44f9acf9242421266329ac8dcb6a88304f5
- Size of remote file:
- 2.89 GB
- SHA256:
- 3af262f8ae3375ddc659731d604243653e02b13831398762ac7e88fb5364b56a
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