사용자 LoRA

XL
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Big Booty Bikini Woman On The Pool Divider

#비키니#수영장
Big Booty Bikini Woman On The Pool Divider - AI Model 커버 이미지
업로드 날짜
2026. 9. 16. 오전 12:33
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트리거 단어

pool, from above, sitting, hand on thigh, arm up, woman, medium breasts, brown hair, ass, red bikini, thong, outdoors, pool, sitting, stone tile, looking at viewer, back, full body, bracelet, earring, hand on thigh, arm up, feet in water, from above

권한
  • 이미지 생성 및 공유 허용
  • 다른 사용자가 내 모델을 다운로드하도록 허용합니다
  • 생성된 이미지의 상업적 이용 허용

설명

At high strengths, this model makes a very specific pose in a specific scene. It's a woman in a bikini with a large booty sitting on a divider between two pools with stone tiles. It started from a single image but I developed a whole dataset from it, mostly adding variations so it'd be less opinionated about elements such as clothing, hair, style, etc. You should be able to substitute whatever character you want into this scene using this LoRA. Have fun!Alternatively, you can make some variant scenes using lower strengths. It can help with things like having a character's feet in the water.This one requires several captions to function properly, but pool is the most important trigger word. from above, sitting are almost as important. hand on thigh, arm up control arm positioning and are needed for the intended pose. So the recommended minimum captioning for the intended pose is: pool, from above, sitting, hand on thigh, arm upMedium captioning is: woman, medium breasts, brown hair, red bikini, thong, pool, sitting, hand on thigh, arm up, feet in water, from above, assThe full captioning is: woman, medium breasts, brown hair, ass, red bikini, thong, outdoors, pool, sitting, stone tile, looking at viewer, back, full body, bracelet, earring, hand on thigh, arm up, feet in water, from abovePlus a few variations on clothing and hair. Adding more of these will make the effect stronger, and you can use them as negative prompts if you have trouble getting what you want to generate.By default, if you get it to generate the scene correctly then it skews towards either the Oatd or the Gerph style, so if you like those styles go give them a look. It's also been regularization trained on Oatd and Galena styles. Oatd in particular shows up if you don't use many captions.

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