Instructions to use LucasDash/dash-wdm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LucasDash/dash-wdm with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LucasDash/dash-wdm", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 264f20a04e91ab148ad52ec4273a260cac46ebf134f7b6fdbd7e713576c1d499
- Size of remote file:
- 335 MB
- SHA256:
- 8988845596f2770db4e2843e8de677cead2a7e04d32660ae0a01b28997bee29a
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