Keltezaa/JizzHere

Doithere

Prompt

a lot of cum

Model description

Since there are already a few really great facial cum LoRAs out there, I wanted to focus CumHereV1 training on a variety of non-facial cumshots. It is intended to produce realistic cum on clothes (sweaters, panties, swimsuits, etc.), breasts, tummy, hair, legs, feet, and more. I did include some Anime and cartoons in the training data but illustrated images produced are hit or miss.

You do not need to include words like "white cum" because it already understands that cum is white. CumHereV1 was not trained on facials but it does randomly drop a load on faces at times.

I am still testing to see how well it plays with other LoRAs. Please leave a comment if you have feedback or find that it doesn't work in a specific scenario.

Usage: Weight of 1 seems to work well most of the time. Adjust the weight down to .8 if you get too much cum but if you set it too low the cum starts to look unnatural.

The LoRA understands what cum is so no trigger word is needed. It usually understands the concept of "a lot of cum" so you can add that phrase if you want more. You will get best results by stating very specifically what you want:

There is cum on her ass and panties

There is cum all over the front of her swimsuit

There is cum on her tummy

There is a lot of cum on her breasts and nipples

There is cum all over her body

I've tested the LoRA with several Flux variants in Forge, SwarmUI, and ComfyUI:

flux1-dev-fp8

flux1-dev-fp16

flux1-schnel - you may need to play with the weight.

These resolutions have been tested extensively but it seems to do well at other resolutions as well:

832 x 1216

896 x 1152

1024 x 1024

Other notes:

Training was about 7 hours on an RTX 4090, for 4000 steps on just 34 images with tightly controlled dimensions across 4 buckets, Learning Rate 2e-4, and very detailed natural language captions.

Trigger words

You should use a lot of cum to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.