Instructions to use Ngene787/Faice_unconditional_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ngene787/Faice_unconditional_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("Ngene787/Faice_unconditional_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
- Xet hash:
- d509a05fa8988054c88750a5cc078e03c4ab94b0dc8bed4868addaefa2da4be4
- Size of remote file:
- 504 MB
- SHA256:
- 687b65500ad80e8fb253150ef70bac81135a2b60e87ccff6a428af3ef9b73e85
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