V4.5角色
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twin turbo (umamusume)

2,554 Danbooru 投稿 · 最高分 606 · V4.5

别名: twin_turbo
seed 1234点击图片放大
NovelAI V4.5 使用「twin turbo (umamusume)」标签的 AI 生成示例图
V4.5NAI Diffusion Anime V4.5
Prompttwin turbo (umamusume), 1girl, solo, best quality, masterpiece, cowboy shot, sfw, fully clothed, looking at viewer

关于“twin turbo (umamusume)”标签

twin turbo (umamusume) 是 NovelAI Diffusion 可以使用的角色标签。Danbooru 上有 2,554 篇投稿,静态图的最高分数为 606。上方示例把这个标签放在固定基准提示词的开头,并以 seed 1234 生成,因此与其他标签的差异都来自这个标签。

各模型画出的 twin turbo (umamusume)

V5

忠实遵循构图和表情的指定,标签效果呈现得较整齐。

V4.5

对标签的反应更强,效果更容易看出来。

ILLUST

本地模型 WAI illustrious SDXL v17。可以看到同一标签在 NovelAI 以外的表现。

twin turbo (umamusume) 在提示词中的写法

先写主体,再写这个标签,最后接质量标签。

基本twin turbo (umamusume), solo, best quality, masterpiece
加画师wlop, twin turbo (umamusume), solo

负面提示词和完整设置请见 使用条款。

示例的生成条件

所有图片都以 832×1216、seed 1234、23 step、k_euler_ancestral 生成。基准提示词和负面提示词对所有标签相同,只替换要测试的标签。被 NSFW 检查判定的图片会换 seed 重新生成或隐藏。

Danbooru wiki 摘录

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Character from Umamusume, voiced by Hanai Miharu.

A reckless, full-power turbo girl with heterochromia and @_@ eyes, who approaches every race by blasting out of the gates at maximum force and almost inevitably burns out by the end; to date, she is the only post-launch character added at minimum rarity to reflect her usual lack of results. Despite her record and childish ditziness, she proves remarkably persistent and insists on treating more talented girls as rivals.

Her personality and style is derived from her real-life namesake horse, who frequently became scared of the other horses he was racing against and flew to the front of the pack to escape, only to run out of stamina and frequently lose; despite poor records, he proved exciting and popular to spectators.

Appearance

Related characters

Team Canopus

External links

来源:Danbooru wiki · twin_turbo_(umamusume) ↗

常见问题

NovelAI 能识别 twin turbo (umamusume) 吗?

请对照本页的示例。本站所有标签都使用相同的 seed 和基准提示词,画面上的差异都来自 twin turbo (umamusume)。

twin turbo (umamusume) 在提示词中怎么写?

把“twin turbo (umamusume)”写在提示词前部,并用逗号与其他标签分开。

V5 和 V4.5 该用哪个?

V4.5 更能体现标签的特色,V5 的姿势更稳定、瑕疵更少。