Instructions to use profpeng/ahegaov2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use profpeng/ahegaov2 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/ahegaov2") prompt = "She does the ahegao face. She sticks her tongue out and crosses her eyes" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2f875f71bf4e41be70f435460b9d242bb25300399875e77a4ccb744115e4c3cd
- Size of remote file:
- 307 MB
- SHA256:
- 8c2b742d70094c9c1024130e2c881558b1e34c61f7b4ae8ccb192082470bf87c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.