Instructions to use sunhaha123/AsiaFaceMix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sunhaha123/AsiaFaceMix 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/AsiaFaceMix", 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 text_encoder/pytorch_model.bin from sunhaha123/AsiaFaceMix: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/sunhaha123/AsiaFaceMix/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://sunhaha123/AsiaFaceMix/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sunhaha123/AsiaFaceMix/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 4f0ae47baa1faac75a1efa543be64c95a8a15268ae9791f9cc94eb095975a1ad
- Size of remote file:
- 492 MB
- SHA256:
- 41aaafa7b6f74e29998b988440ae2f21fbf1a13918c1495717fafa0f9ae245b2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.