Pussy Spread
Pussy_Spread_FLUX.safetensors LORA / Flux.1 D
- Model Name
- Pussy Spread
- Version
- v1.0
- Creator
- Neuroger
- Size
- 36.66 MB
- Downloads
- 5,934
- BTIH
- 84C59521BAA13CDD130886C17F6FB0C47F121800
- BTMH
- 95EA255D4612DFDC015106AC65AA8E72F2724390E2E23C4E428FD45EE6EE8EC7
- SHA256
- EC1EA48F60E3F6077E3461993FD579A6F5D198D11217F021566B7A050FFACCAD
- Upload Date
- about a year ago
- Uploader
- CivitasBay.org
- Status
- 3 Seeders0 Peers
This LoRA model allows you to make women who spread their vaginas with their hands. Showcased images are using only this LoRA. For better breasts, you should add another LoRA for that.
Unfortunately, with GGUF versions, the success rate is lower.
Prompting guide:
1: Main trigger:
“A wide shot of a fully naked woman lying down on a bed and spreading her vagina with her hands.” Or “A bottom view of a fully naked woman spreading her vagina with her hands.” If you want a face-sitting effect
You can add some general description like ethnicity for the woman like “…naked Caucasian and slim woman…”
2: Vagina description:
Describe the vagina, shaved or short/long pubic hair, and even if there is a wide opened hole.
“Her pink vagina is very hairy with long pubic hair.” Or “Her vagina with darker lips is perfectly shaved” or “Her widely opened with a wide-opened vagina hole vagina has been recently shaved”
3: Hands description:
You can describe the hands, nail length, etc.:
“Her pale hands have medium-sized natural nails.” Or “Her slender hands have long red nails.”
4: Woman description:
Now you can add more details to the woman, like breast size, facial expressions, and clothes:
“The woman with medium-sized breasts looks at the viewer with a wide smile.”
5: Environment:
Describe where the scene occurs:
“The scene occurs in a typical Japanese bedroom filled with natural daylight.”
6: Bonus: Anus:
Not working great but the anus description has been captioned so you can add “Her anus under her vagina is tight, with slightly darker skin and short hair.”
Training and dataset:
50 high-quality real images (close-ups and wide shots) of 1024x1024 sized down (Lanczos) to 512x512. Handmade captioning. Default Civitai training settings except for Epochs.
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