Instructions to use umikaze/daybreakdiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use umikaze/daybreakdiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("umikaze/daybreakdiffusion", 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:
- b113003322463c41cfaeec18081753e552a2880a6b1447b1b715bbe4b3bdcb54
- Size of remote file:
- 3.44 GB
- SHA256:
- b1669ce991f0cf7a645c7e809e58124832ef7b2a37278407a78965d60c5248de
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