The English portion is translated by GPT and may contain errors.

值得注意的是，在该模型的训练中，我使用waifuc来通过搜集和处理训练集，他可以轻易过滤掉我所不需要的双人图，杂图和黑白图片，这使我的训练集的质量得到提高。

https://deepghs.github.io/waifuc/main/tutorials-CN/installation/index.html

It is worth noting that in the training of this model, I used waifuc to collect and process the training dataset. It can easily filter out unwanted images such as double exposure, miscellaneous images, and black and white images, which improves the quality of my training dataset.

https://deepghs.github.io/waifuc/main/index.html

全标训练

使用DIM4训练，体积大小只有27M左右

Full mark training.

Training with DIM4, the volume size is only around 27M.

训练模型：SDXL1.0官模

测试模型：Kohaku-XL

建议权重：0.8 or adjust them freely according to the situation.

触发词：xingqiu_\(genshin_impact\), 1boy, male_focus, solo, jewelry, earrings, blue_hair, smile, simple_background, white_background, looking_at_viewer, single_earring, yellow_eyes, bangs, frilled_sleeves, frills, water, long_sleeves, short_hair, chinese_clothes, upper_body, eyes_visible_through_hair, asymmetrical_bangs

推荐模型：Kohaku-XL ， X2 Anime 二次元通用模型 【Final】

Training model: SDXL1.0 Official Model

Testing model: Kohaku-XL

Recommended weights: 0.8 or adjust them freely according to the situation.

keyword：xingqiu_\(genshin_impact\), 1boy, male_focus, solo, jewelry, earrings, blue_hair, smile, simple_background, white_background, looking_at_viewer, single_earring, yellow_eyes, bangs, frilled_sleeves, frills, water, long_sleeves, short_hair, chinese_clothes, upper_body, eyes_visible_through_hair, asymmetrical_bangs