Update: Turns out this LoRA is a damn pansexual and can create hetero content, if so prompted. I guess I should be supportive of its digital life choices despite my sus dataset training. Deep down I suspect this is my husband's doing with his sportsball watching and whatnot - that and its ZIT genetics.

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I created a LoRA to assist creating scenes of nutsack worshiping since Z-Image (and Flux) generally will create scenes of mouth-on-penis despite specific prompting. I've noticed that of the checkpoints I regularly use, you might get the concept eventually with the right seed (heh), but usually requires the use of CN or a second pass inpainting run.

Well now your boys can get that lovin' attention they so deserve with this little number.

The dataset includes about 440 HQ images to get a good diversity during the training process. I used a large dataset because of ZIT limitations on using multiple LoRAs, I made sure there was a varied viewing perspective of peens of all types (uncut, cut, big, small, black, white, with or without cock ring, thick pubes, no pubes, etc.). So, with Z-Image's strong prompt adherence in general, using this you can specify things like licking, sucking, smelling, covering face / eyes / nose, on forehead / head, etc., and get good results of the full .. package. One note is uncut peens might take a few more generations if that's what you're going for. If I create a new version I'll correct that imbalance in the dataset.

It shouldn't need a trigger word but it can help, and even short prompting can generally yield good results so long as you give a little direction.

Images in gallery are all txt2img generations without img2img 2nd pass corrections.

I recommend strength about 0.8 for a more realistic skin texture.