UPDATE 1/31/2025
Last merge had to be removed due to model permissions. Remerged with different model.

Merged Loras:

• My Edge of Reality Lora - https://civarchive.com/models/1129944

• HunyuanVideo POV Titjob / Paizuri by KaptainSisay - https://civarchive.com/models/1114844/hunyuanvideo-pov-titjob-paizuri

Trigger words: [amat_petite], titfucking

Likes the phrase: "giving a titfuck, She squeezes both of her breasts together and puts the mans penis between her breasts she moves her body up and down titfucking the penis with her breasts."

Example prompt in version notes

UPDATE 1/23/2025

Merged Loras:

• My Edge of Reality Lora - https://civarchive.com/models/1129944

• Hunyuan Video handjob Lora by cavemanman333 - https://civarchive.com/models/1118309/hunyuan-video-handjob

Trigger words: [amat_petite], handjob, stroking

Likes the phrase: "a woman giving a handjob to a man stroking it up and down with her right hand" to generate a handjob.

Example prompt in version notes

A LoRA designed to help style amateur videos with unique options for body types, clothing, and small details. Trained off of an old dataset of from a FLUX LoRa I left unfinished. I didn't change any of the captions from the FLUX dataset and honestly I'm shocked how well it came out. I ran it as an experiment expecting to throw it away and needing to re-caption.

This LoRA is INTENDED to give a slightly lower quality output more similar to cellphone videos in general.

Civitai Video compression did a number on these videos for some reason. Weird coloring coming through... They look better if you click the image vs just the preview window.
Example of non-strange coloring: https://files.catbox.moe/m5zxii.mp4

Main Trigger Word: [amat_petite] (trained with the [] so they may be necessary)/
See all training captions here: https://files.catbox.moe/rwj3po.txt

What it's good at:

• Amateur video styles such as cellphone video and selfie angles

• Petite body types

  • Skinny, thin, shirt, tall, can get others out of it but it will skew towards petite.

• Wide range of breasts

  • sizes but skews towards small breast sizes, has a harder time with large breasts

• Various poses

  • Kneeling, Standing with arms above ahead, reclined on bed/couch, running hands along body through hair, squeezing/holding breasts, hands on hips, general photography model posing, side profile

• Tan lines

  • Very good at tan lines, lots of examples in the training set

• Skin Shades

  • Trained all on Caucasian subjects but you can get a good range of skin tone from pale, average to tan.

• Braces

  • The original dataset had a few training images with braces and honestly they work pretty well, can be a little noise if the video shot is too wide

• Clothing in pulled down/up states

  • But it's not great at the actual motion of pulling it

• Hair

  • In general the motion of hair is pretty good, even if the subject is interacting with it

• Different lighting types

  • Best at natural light, should understand: "outdoor light, natural light, indoor light, overexposed

What it's okay at:

• Facial/Cum on Face

  • There were a couple training images of it, IMO it's a little too thick and doesn't flow well but it's an option

• Ahegao

  • Not captioned as Ahegao but "mouth open with tongue sticking out," gets you there

• Rear Facing

  • Okay with the subject facing away from the camera but there wasn't much in the training data

• Adjusting clothing/underwear

  • Can have the subject slightly adjust their underwear without unrealistic movement

• Closeup shots of breasts with head out of frame

What it's bad at / Issues

• All the backgrounds were photoshopped out of the training images which leads to the model outputting the subject with a plain white background (which could be interesting for chroma keying the subject for video edits)

  • This can be avoided by describing the background in detail

  • It also sometimes leads to the subject looking like it's unnaturally dropped into a static background

• If you use the word "photo" you will get an static video or in very slow motion.

  • This is likely because I captioned the images with things like "professional photo", "cellphone photo", "home photo"

  • including the word video in the prompt helps

• Actually removing clothing with motion

  • Tends to make the clothing really twisted and strange.

• Occasionally puts in tattoos but I don't recall any of the training data having tattoos, none of the training captions included tattoos. I've noticed this effect in other LoRas I've trained as well. I think Hunyuan training occasionally interprets bracelets, clothing logos and necklaces as tattoos, especially when small and not captioned

I've included a ZIP with a TXT that has all the training captions so you can see what you're working with in terms of prompting