description: <p>2.0 SDXL verson:</p><p>使用了1000张图片训练。</p><p>Training model: Animagine XL V3</p><p>Inference model: Animagine XL V3</p><p>Training resolution: 1024*1024</p><p>Recommended output resolution: 1024*1280</p><p>Recommended model weight: 0.8~1</p><p><span style="color:rgb(193, 194, 197)">特别鸣谢：算力赞助 / GPU Sponsor: </span><a target="_blank" rel="ugc" href="http://nieta.art/">nieta.art</a></p><p><strong>The English portion is translated by GPT and may contain errors.</strong></p><p>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。</p><p><a target="_blank" rel="ugc" href="https://deepghs.github.io/waifuc/main/tutorials-CN/installation/index.html">https://deepghs.github.io/waifuc/main/tutorials-CN/installation/index.html</a></p><p>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.</p><p><a target="_blank" rel="ugc" href="https://deepghs.github.io/waifuc/main/index.html">https://deepghs.github.io/waifuc/main/index.html</a></p><p>喜多，喜多</p><p>全标训练</p><p>使用DIM4训练，体积大小只有27M左右</p><p>Full mark training.</p><p>Training with DIM4, the volume size is only around 27M.</p><p>训练模型：SDXL1.0官模</p><p>测试模型：Kohaku-XL</p><p>建议权重：0.8 or adjust them freely according to the situation.</p><p>触发词：1girl,solo,red_hair,white_background,shirt,long_hair,green_eyes,one_side_up,bangs,hair_between_eyes,yellow_eyes</p><p>推荐模型：Kohaku-XL ， X2 Anime 二次元通用模型 【Final】</p><p>Training model: SDXL1.0 Official Model</p><p>Testing model: Kohaku-XL</p><p>Recommended weights: 0.8 or adjust them freely according to the situation.</p><p>keyword：1girl,solo,red_hair,white_background,shirt,long_hair,green_eyes,one_side_up,bangs,hair_between_eyes,yellow_eyes</p>
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name: Kita Ikuyo XL 喜多郁代  きた　いくよ    孤独摇滚
tags: character bocchi the rock!