Features

• Compatible with both T2V & I2V Wan2.2 Models

• Trained on simple word tags: vagina, anus, ass

Tips

• Look like strength between 0.5 to 1 is good. I normally use 1 for I2V but others are mentioning that 0.5 works, too.

My Wan2.2 Cover Videos

Workflow is T2I SDXL/Flux/Pony -> Image Upscaler -> Wan2.2 I2V -> Upscaler -> Add FPS

https://civarchive.com/models/1916073 (text2img & img2vid). Credit DonutsDelivery & Daxamur

https://civarchive.com/articles/14582/comfyui-workflow-sdxl-facedetailer-upscaler-and-batch-selection (text2img)

Training

Trained on Wan2.2 T2V base model. 50 high quality images and 50 videos that were handpicked and farmed raised to perfection using musubi-tuner. This LoRA works with both I2V and T2V.

Limitations

The dataset contained videos with hand movement like rubbing legs or rubbing breasts. Some of the videos also had slow hand motions. You may need to prompt to remove or proactively address by saying where the hands go, e.g. hands stay still, hands are still, hands rub her legs.

Pussys are extreme complex. No two pussys are the same so the model struggled at some points to fully generalize the pussy's complexity. More training may be required in the future.