Instructions to use sunhaha123/AsiaFaceMix2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sunhaha123/AsiaFaceMix2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sunhaha123/AsiaFaceMix2", 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 vae/diffusion_pytorch_model.bin from sunhaha123/AsiaFaceMix2: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/sunhaha123/AsiaFaceMix2/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://sunhaha123/AsiaFaceMix2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/sunhaha123/AsiaFaceMix2/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 3b8eabdd7d1b15cc93f3ea69bc30ed6767421f2b41e6751010e7111cb5fb4665
- Size of remote file:
- 335 MB
- SHA256:
- 07c2c381f6e411672f9940a4b919619cc1dbea6d6ee920596868f84301aadcf2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.