WAN t2v and i2v are identical. Just uploaded twice for on-site generation to work.
This LoRA is trained on conversational language. You can describe your scene in plain English or Chinese, and it should adhere to your prompt well. Below are some inspirations for you if you need it.
Positions:
On her back
Kneeling
Perspectives:
POV
Enhancement phrases:
She bounces her body up and down
She bounces her breasts up and down with her hands
All showcase videos have the workflow metadata embedded. You can download the video and drag it into ComfyUI to replicate them with their prompts, seeds, and settings.
Description
Includes better nipples, under clothing variation, and better adherence for side-view angles. Additionally, you won't have to be as overly descriptive with your prompts to keep the penis between her breasts. The LoRA now understands that Titfuck means "penis between breasts" usually.
This version was trained using the following configuration and dataset settings:
26 videos 4-5s long each. 256x256. Downscaled using bicubic to minimize pixelation
200 Epochs, each video is processed once per epoch.
Learning rate of 2e-5
Captions had reduced redundancy (removal of "penis between breasts" and other overly descriptive elements) to allow the LoRA to increase association with "titfuck" instead of other tokens.
Introduced more side-view videos, videos that included better nipple detail, and titfucks with clothing (bikinis, sports bras, etc)