About this version (qwen v2)A brushup of the dataset, with better result than V1 for qwen. I will use the same dataset again for zturbo when the base model is released. Trigger word: PENISLORAWhat can this lora do?This lora can add erect penises to both men or women viewed from the front/side. Other angles such as POV may have a backwards penis head. Other things it can now do: Side view of the penisCumming / CumshotsBlowjobs (its captioned for the words "blowjob" and "deepthroat" )What can't it do?No penetration in the training data. Also nothing from POV angle, though there is a few images from above and 1 POV video in the training data.Sometimes blowjobs with cumming have the penis slip out the closed mouth.Recommended SettingsIt works pretty good with the new lightning dyno high model. I'll link to it in my example workflow. I like to use dyno high model (no lightning lora), then for low I use the lightning v2 lora on the regular 2.2 low base model.Dataset84 images at 512x resolution43 videos at 256x resolution(I let DP pick the aspect ratio automatically)This is the same exact dataset as the 2.2 5B model. I made no changes.TrainingI used the default diffusion pipe settings.[optimizer]type = 'adamw_optimi'lr = 2e-5betas = [0.9, 0.99]weight_decay = 0.01eps = 1e-8I was baffled why it was taking so long to train the high until I realized after over 60 hours of training that I had put my videos in the images directory which resulted in the high being trained ONLY only on videos and twice (once with a very high resolution). Once I fixed this, I went back and trained from 11K steps up to around 13K with the images in the training data. The high model was fine without to be honest.For the low, I trained it properly with videos and images the whole way, around 6K steps in I upped the image resolution from 512 to 1024 actually and didn't get an OOM (it fit around 24GB exactly). I trained it to around 10.5K steps. Also I trained the low on the full timestep range (0 to 1 instead of 0 to 0.85) from some advice, it may switch better over from high to low on the speed up lora with low steps.I think I might do another version with more angles such as POV and from the behind to make this work for any situation. In that case I don't think it needs 10K steps per training session, epochs around 5K steps looked fine.The resultsI think it was a combination of improved captioning and 2.2 base model being better. But this lora turned out really well.

Penis Lora (+Blowjob, +Cumshot) [Taz]  - WAN 2.2 14b / 5B / 1.3b T2V & I2V (Wan 2.1 & 2.2) + Qwen + Zimage Turbo

Trigger: PENISLORAThis is a 1.3B T2V version of my penis lora. It does for the most part everything the 14B version does(though a bit more poorly).Its trained to 90 epochs (that's over 90 hours of training locally on my 3090...) at 5 repeats and 19,600 steps. I think I will do one more run over night for 100 epochs, but for now will release as v0.7b. There should be no reason to use v0.7a at this point.Check the example workflow for ideal settings. I kept things at 1 strength but I think you can play around with it. I didn't do much experimentation. And a big thanks to the help from everyone including Kijai at the banodoco discord for how to properly set 1.3B settings.Check the example generations for example prompts or try from those listed in 14B v0.7 lora.1.3B is kinda fun with how fast you can shoot out gens, but there is obvious limitations with this model. After 0.7c is released, I think I am going back to 14B and working on getting that to a good place before I revisit this again.

Files with SHA256: b1eccab35fa96938c86c35c6da258adeca25c594cc9991453fcfdfe5713fd96e