Wan 2.2 v1 (T2V) This is incredible. I did make a few changes to the dataset, added a few variety pieces, and I trained on 720p this time, but... I think the improvement is all Wan 2.2. Can't be certain, but... I'll let the samples speak for themselves.Also, thanks to K3NK for the ridiculous workflow! v1.1 (T2V) This one is absolutely a one-trick pony, but that's kinda the point, right?All of my videos always save the ComfyUI metadata, so right-click / drag-and-drop for a starting point! v1.1 (I2V) Same dataset as the T2V model, just trained on the 480P 14B model.<ul><li>I2V seems to like higher shift, 12-15</li><li>it also seems to like higher CFG, like 6</li><li>oh, and a lower model weight on the LoRA, like 0.8</li><li>Experiment, and let me know / share your results!</li></ul>a.k.a "The Adriano Angle"... IYKYK.Post what you've got with this, I'd love to see some other successful prompts! My first LoRA upload... This is WIP as I've been learning, but I figured I'd share what I got for feedback. For images, I use the absolutely fantastic <a target="_blank" rel="ugc" href="https://civarchive.com/models/722045/tame-pony-the-authenticity-machine">TAME Pony</a>, which I don't think gets anywhere near the credit it deserves. I followed <a target="_blank" rel="ugc" href="https://civarchive.com/user/dtwr434">dtwr434</a>'s very helpful Training Data guides for training WAN loras with diffusion-pipe, in fact I don't think I changed any settings at all for this one.

Anal Missionary Wan (2.2!)

Trimmed down the dataset a bit, re-captioned with a much better approach, and trained for 100 epochs. This one works WAY better T2V.

Files with SHA256: 7458f0e28c1dc5584617b3f255427f1c310f954f56d0059e631af1d38c4cd165