Instructions to use profpeng/cumonface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use profpeng/cumonface with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-I2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("profpeng/cumonface") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 57f191d4ee6e270c5ccb38581e0f861945d4a52f7dad48c0a442779fb1dc3e76
- Size of remote file:
- 307 MB
- SHA256:
- b40be97c9c593e9539f8116e3e70f1c94f956b9ec55c679b65347d7a890679dd
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