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V1.0_pynoise
Umi Kousaka/高坂海美 | MILLION LIVE!/ミリオンライブ/ミリシタ

Umi Kousaka/高坂海美 | MILLION LIVE!/ミリオンライブ/ミリシタ

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#Character
#ผู้หญิง
#ตัวละครในเกม
#idolmaster
#million live
#idolm@ster

LoRA model of Umi Kousaka (高坂海美) from media-mix project THE IDOLM@STER MILLION LIVE! (アイドルマスターミリオンライブ!).

The trigger word is umi kousaka (million live). Considering the Second Hair Style (SHS) card in Mirishita, this model don't fix Umi's hairstyle. You can reproduce the Umi's style of game card illustrations by adding following tags:

*Original hairstyle of Umi:

twin braids, long hair

*Second Hair Style of Umi:

 high ponytail, side ponytail, long hair

Of course, you can change features of hairstyle at your own. Try and enjoy it!

The LoRA weight of samples is 0.8-0.85; you can also try other weights. The greater the weight, the closer the character style is to the game card of THE IDOLM@STER MILLION LIVE! THEATER DAYS (ミリシタ) and the new tachie drawn after the release of the game.

Note: I load my LoRA model through the additional network WebUI plugin, so the prompt of sample illustrations don't contain <lora:XXX:X> tag.

I'll appreciate it if you're willing to use this LoRA model and share AI arts to other people. My models and illustrations are free for everyone, and if you like them, please support me at Patreon or 爱发电.

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跨媒体企划《偶像大师 百万现场》的角色高坂海美的LoRA模型

模型的触发词为 umi kousaka (million live)。考虑到游戏的第二发型卡(SHS),本模型没有固定海美的发型特征,您可以通过添加以下标签来复刻游戏卡面中海美的风格:

*无印卡面的海美:

twin braids, long hair

*第二发型卡的海美:

 high ponytail, side ponytail, long hair

当然,你也可以自由改变发型特征,敬请享受!

示例图的LoRA权重为0.8-0.85,您也可以尝试其他权重值。权重越大,角色风格越接近游戏《偶像大师 百万现场 剧场时光》(MLTD)游戏卡面以及该游戏发行后新绘制的立绘

我使用的是WebUI的可选附加网络(additional network)插件,所以示例图的prompt里并没有<lora:XXX:X>的tag,还请注意

如果您愿意使用本LoRA模型并将作品分享给其他人,本人将不胜感激。本人制作的所有模型和绘画皆免费提供,如果觉得还不错的话,欢迎在Patreon爱发电上支持我,非常感谢。

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2024-04-02
Pubblicare modello
2023-08-07
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Dettagli modello
Tipo
LORA
Data di pubblicazione
2023-08-07
Modello Base
SD 1.5
Parola Chiave
umi kousaka (million live)
twin braids, long hair
high ponytail, side ponytail, long hair
Copia
Introduzione alla versione

V1.0_pynoise: Initial release. Model trained using DAdaptLion optimizer, with multi-resolution noise and minimal SNR gamma enabled.

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Model Source: civitai

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