Wan 2.2:This model was trained using ai-toolkit with 20 81-frame 16-fps videos.Wan 2.1:Optional: You can optionally use the "NEGATIVE" version of this lora (with a negative value around -0.5) to that can help combat failed generations like her penis disappearing.Positive Prompt Example: Trans woman laying down. Thrusting all the way in and out of her asshole. Her penis is erect. Anal penetration. The camera stays stationary. She has her eyes open.Negative Prompt Example:Overexposure, static, blurred details, subtitles, paintings, pictures, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, mutilated, redundant fingers, poorly painted hands, poorly painted faces, deformed limbs, fused fingers, cluttered background, three legs, logo, text on screen, vagina, deformed penis, motion blur, blurry penis, eyes closedThis model was trained with 37 2-second videos at 16fps.I'm aware that it's the general convention to train on the T2V Wan checkpoint, but I get bad results (with both T2V and I2V) when I do so with this particular dataset.

Wan 2.2 / Wan 2.1 - Trans & Futanari Missionary - I2V

This version is to be used as a NEGATIVE lora along with the normal v1.0 version to combat the effect of the disappearing penis. This was trained on about 100 failed generations of different iterations of the v1.0 lora.I tend to use a strength of 1.0 on the normal lora and -0.5 on this version. However, more experimenting can be done to get the best tradeoff between motion and the disappearing penis effect.

Files with SHA256: e327473829e6b5e4df1000507994df8aa1d5031f7bceb15e1215e2651100fcf2