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v4 ZIT
v4 WAI_IL
v4 noob_vpred
v3 pony
bubble_butt SDXL/ZIT

bubble_butt SDXL/ZIT

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#개념
#thick
#???
#booty
#thicc
#풍선 ???
#하이퍼
#Illustrious

This LoRA generates bubble butts for a number of SDXL/ZIT models. Its nearly the same dataset as my SD1x bubble ???? but with a handful of larger sizes added, and better tagging.

Use the tag "bubble ????", with (optionally) one of the following size tags "medium ???", "big ???", "huge ???", "gigantic ???", "hyper ????" along with similar Hyperfusion tags.

If you want front facing images try "from front", or "??? visible from front" and negative "???????????, looking back, ?????????" at varying weights.

v4 ZIT Changelog:

  • Couldn't resist training a lora on Z-Image-turbo. Went pretty well, so ill probably be training more when the base model drops.

  • This one is just a quicky, probably not fully trained, but good enough as you can see.

  • Dataset is fully anime/furry, so you need to include realism related tags and words if you want that.

v4 WAI_IL Changelog:

  • No changes, just re-trained on WAI_IL-v14 because I was in a tinkering mood.


v4 noobai_vpred Changelog:

  • Not much changed. Added a few more images/captions/tags, and trained on noobAI_vpred_1.0 with somewhat similar settings to v3

  • Same tags as v3, you already know what to expect

  • "hyper ????" has a greater effect on this noob_vpred version as well if you want it really large.

번역문 보기

평점 및 리뷰

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T
공고
2024-04-02
모델 게시
2025-12-03
모델 정보 업데이트
모델 상세정보
유형
LORA
게시 날짜
2025-12-03
기본 모델
ZImageTurbo
트리거 단어
bubble butt
복사
버전 소개

Just a quick bubble ???? lora on the new Z-image architecture. Ill do a full lora when the base model comes out, but I couldn't resist trying it out before then.

Pretty happy with results. Didn't require any tinkering. But I did need to use the ai-toolkit lora adapter to get stable results.

Same dataset as the last.

Training Details:

train_text_encoder: false

  • type: "lora"

  • linear: 16

  • linear_alpha: 16

  • conv: 8

  • conv_alpha: 8

  • caption_dropout_rate: 0.1

  • resolution: [ 768, 1024 ]

  • flip_x: true

  • batch_size: 1

  • gradient_accumulation: 8

  • optimizer: "adamw8bit"

  • lr: 4e-4

  • dtype: "bf16"

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모델 출처: civitai

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