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:
- c118233c3fde007e2844a9ab9ea556af5d6841a2cba72213773382c65c1c9623
- Size of remote file:
- 439 kB
- SHA256:
- 6583919f5ca09bc2546d302595ec65d1b1b09bb54f1b20ebdbe9d295f715467e
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