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", torch_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:
- d985810730d15b1b1f2d4150a4f1deba50ee7766e2da1a21a7c3330de402f916
- Size of remote file:
- 492 MB
- SHA256:
- 653c2914edc2bd978e9424f7d928ecaa45b9d0cf3e610f54d75b40db052c0cd7
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