Instructions to use d-wang26/wd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use d-wang26/wd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("d-wang26/wd", 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:
- 35e1c77e84476910f64ce32f493139a12da2080b48dc1b8221ed4ae5c8aca2bb
- Size of remote file:
- 6.04 MB
- SHA256:
- 57b0e42867c8437d948c9a11237aafe9aa42cde0bd3dc9b4bf92fc4767f64271
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