Instructions to use Ching2602/wanfacesitting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ching2602/wanfacesitting 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("Ching2602/wanfacesitting") prompt = "A woman places her crotch over the camera, obscuring the view. The final frame of the video is a close up of the woman's crotch" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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("Ching2602/wanfacesitting")
prompt = "A woman places her crotch over the camera, obscuring the view. The final frame of the video is a close up of the woman's crotch"
image = pipe(prompt).images[0]wanfacesitting

- Prompt
- A woman places her crotch over the camera, obscuring the view. The final frame of the video is a close up of the woman's crotch
Trigger words
You should use A woman places her crotch over the camera to trigger the image generation.
You should use obscuring the view. The final frame of the video is a close up of the woman's crotch to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Base model
Wan-AI/Wan2.2-I2V-A14B