Instructions to use yee-haw/weewojei with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yee-haw/weewojei with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yee-haw/weewojei", 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:
- cdc0e04e4735b6924875c0f8c355579030fd4036479e9bc3ee3505e21fb06b7e
- Size of remote file:
- 910 MB
- SHA256:
- 2f3ff4336abeb6ca19cbf49419798ab06064e0c92410e3860a3345deaa676716
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