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:
- a7da7192fbc93a371a3994f7ffb7adfb904d81637b5439a1d4fc0df585cc93f2
- Size of remote file:
- 2.89 GB
- SHA256:
- cbb168a5b32729cabc5c5203e34e857fdfdf697fbcbc682be962f0c76b232080
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