Instructions to use miittnnss/diffusion-faces with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use miittnnss/diffusion-faces with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("miittnnss/diffusion-faces", 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:
- 7833ec665ef07c249c16f06cefca76c7e151885d0001d2a150ea106255495b61
- Size of remote file:
- 493 kB
- SHA256:
- 7ac963868e39cbf2f01db749de75ad5c8b7fb5354a4caca0bdc73bc1d43d4ce9
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