Instructions to use Snowad/Eminence-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Snowad/Eminence-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Snowad/Eminence-Diffusion", 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:
- f50bd6f7461f83ac61ceaed55488e866dfc976ea5f3be7d3026c826347c64115
- Size of remote file:
- 492 MB
- SHA256:
- 7aa21681623c3ee543613522498aa2da4ce213fbe0762d5688c59493311fe6d5
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