Instructions to use lunarfish/furrydiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lunarfish/furrydiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lunarfish/furrydiffusion", 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:
- fba81f5fa9c89fed3849a6d9fbf8feb2a638fd9fefe89860ffdd3e18b99327b6
- Size of remote file:
- 246 MB
- SHA256:
- 27fca8794fef9738a38ea9f2ac3cd8e0382f5ba1606e2fa2f4cb81469cdc6064
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