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사용자 LoRA

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Clothing: Angrakha | Indian Male Attire

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Clothing: Angrakha | Indian Male Attire - AI Model 커버 이미지

무료 가입 후 10,000 크레딧을 받아요!

가입 당일 계정에 지급되는 창작 크레딧!

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업로드 날짜
2026. 11. 3. 오전 3:48
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6
리뷰
리뷰 없음
트리거 단어

angrakha, paisley print, long ornate tunic,

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추천 LoRA

설명

Disappointed but not surprised that Illustrious models have little idea of Indian clothes, especially male ones. So, I tried to make this lora myself. This is the prototype version, and it takes a bit (lot?) of playing around with prompts and weights to give the best results.This lora was particularly trained on a specific angrakha design I find interesting, though it can generate normal asymmetric kurtas too. That style of angrakha is based on a portrait of Wajid Ali Shah, a historic ruler who used to wear the garment such that it deliberately left a nipple exposed. It wasn't easy to achieve this look, but after a lot of trial and error, I've found the model is good enough to be shared.Recommended Weights: 0.7-1.0Recommended Positive Prompts: male focus, 1boy, angrakha, indian, asymmetrical clothes, high collar, waist sash, ornate long tunic, ornate pleated skirt, leggings, patterned clothes, paisley print which can be paired with two different styles, the more conservative diamond cutout and the infamous slanted cloth cutout, single bare pectoral, single nipple slipRecommended Negative Prompts: important detached sleeves, detached collar, bare shoulders, bare arms, bare back, bare legs, asymmetrical legwear, bad anatomy, bad hands, bad eyes, native american along with standard lowres, bad quality, 1girl, multiple girls, breastsGood Prompts to Include: any combination from among bishounen, bara, skinny, chubby, muscular, embroidery, ornate clothes, ornate, gold trim, gold, silver, jewelry, pearl necklace, embroidered footwear, embroidered clothes, print shirt, print skirt, glitter, silkCreator's Notes: Results may greatly vary with different models and lora combinations used, even I'm not sure I've found what would make the most consistent generations 😅 I've noticed it does better on 3-4 cfg and 0.8-0.9 denoise.

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