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:
- acf0c47738c02a2609ba17b39a33386c8e59fcbf0068595d461feda628459320
- Size of remote file:
- 2.89 GB
- SHA256:
- 0bacb7e7d7090b6ffc5fdc9fe640d4910989f6ed7b2e3ec8089e41f02b918165
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