Instructions to use michaelz/ArcaneFace-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use michaelz/ArcaneFace-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("michaelz/ArcaneFace-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
Download unet/diffusion_pytorch_model.bin from michaelz/ArcaneFace-Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/michaelz/ArcaneFace-Diffusion/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://michaelz/ArcaneFace-Diffusion/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/michaelz/ArcaneFace-Diffusion/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 211fe6af1124bc4a27242fd462fcaf89a1b8e23dcbf82d9168639a070a7c05db
- Size of remote file:
- 3.44 GB
- SHA256:
- 69d61b7a0bffe38b24fdb531d2159e5cc38e1555fe6868486a0e86f3acc4de72
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