WARNING: Only works with the Sulphur LTX 2.3 model
Trigger word: PENISLORA (put it at the front of the prompt)
Stroking: "The man is stroking his erect penis. The penis is visible from the side"
Blowjob: "The woman is giving a deepthroat blow job to the man's erect penis. The penis is visible from the front"
Trained on 215 clips of penises from the front view and the side. With no audio.
Prompt "The penis is visible from the side" for side view of penis head.
Prompt "The penis is visible from the front" for the front view of the penis head.
It is not trained on POV view of the penis at all. It has no training data on penetration or cumming.It has blow job and deepthroat in the training data as well. But its mainly for giving details to the penis and stroking. It also can be prompted without stroking.
This is trained on the NSFW LTX dev merge of LTX 2.3. It will not work on the regular model. I have only tested it with the full dev model not the lora version. Strength 1 works great, us the example workflows provided by a kind gentleman. Swap out the LTX base model for the sulpher dev model and put the lora on both passes.
I trained it up to 20k steps, but it had an amazing result at 4.5k steps. Previous attempts on the BASE model of LTX took 20-30k steps for a worse result. Please train NSFW on this model from now on. I trained it on rank 48, and for some reason it trained very fast. 1.3 s/it. This lora was basically done in an hour or so. I may test other checkpoints later, but 4.5k steps seems good enough for now. It's trained on the default layers for t2v, not tested in i2v. I could do a i2v version maybe if there is enough interest.
Description
I trained on top of the 4.5k checkpoint with 80 additional images. These images should act like a detailer to less plastic-like skin on the penis, and give better shape on the head. I've had better looking results on the front view.
I think 8k has better penis shape, but breasts come out and are more stiff. I think 6k is a little undercooked, 7k steps version may be best. I put all three out here.
FAQ
Comments (1)
V1.1 has over trained on the breasts in the dataset somehow... I will do another fix by training the images + videos together and removing some images.