Instructions to use michaelkmccoy/dbkw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use michaelkmccoy/dbkw with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("michaelkmccoy/dbkw", 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:
- 1ca5cf5b088cd940db3a4256a1837192e126b9621ffe971773205f0a42b3942f
- Size of remote file:
- 492 MB
- SHA256:
- 7e3e7a17358024bd8dd85a7b437fbdb599b7e58483a57ea90d17808f7b559505
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