Trigger word:<span style="background-color:rgb(10, 10, 10);color:rgb(238, 238, 238);font-family:&quot;JetBrains Mono&quot;, &quot;Fira Code&quot;, &quot;Cascadia Code&quot;, &quot;IBM Plex Mono&quot;, &quot;SF Mono&quot;, Consolas, Menlo, &quot;Liberation Mono&quot;, &quot;Courier New&quot;, &quot;PingFang SC&quot;, &quot;Microsoft YaHei&quot;;font-size:13px"> <code>@fhbpn</code><span style="background-color:rgb(10, 10, 10);color:rgb(238, 238, 238);font-family:&quot;JetBrains Mono&quot;, &quot;Fira Code&quot;, &quot;Cascadia Code&quot;, &quot;IBM Plex Mono&quot;, &quot;SF Mono&quot;, Consolas, Menlo, &quot;Liberation Mono&quot;, &quot;Courier New&quot;, &quot;PingFang SC&quot;, &quot;Microsoft YaHei&quot;;font-size:13px">把画师 Boppin 的原创画风固化成单个 LoRA。干净的扁平动画风——清晰的黑色描边、平涂配简单渐变阴影、明亮通透的配色、大眼简化面部，背景常是白底或青海波一类的装饰纹样，人物体型偏娇小。这是我第一次尝试炼制画风 LoRA<span style="background-color:rgb(10, 10, 10);color:rgb(238, 238, 238);font-family:&quot;JetBrains Mono&quot;, &quot;Fira Code&quot;, &quot;Cascadia Code&quot;, &quot;IBM Plex Mono&quot;, &quot;SF Mono&quot;, Consolas, Menlo, &quot;Liberation Mono&quot;, &quot;Courier New&quot;, &quot;PingFang SC&quot;, &quot;Microsoft YaHei&quot;;font-size:13px">（也是第一次直接拿真人画师的作品当数据集，之前只炼过自己渲染的图），成色上还有进步空间，请多包涵。底模需与训练底模一致（anima-base-v1.0）<ul><li>提示词以 <code>@fhbpn</code> 开场，权重 0.8 ~ 1.2（1.0 最接近原味，1.2 线条更明确、风格更浓）</li><li>采样 30 步 / CFG 3.5~4.5 / er_sde + simple</li><li>务必接放大链路：一采之后用 SesquiLatentUpscale ×1.5 → 二采 10 步、denoise 0.35。这画风的看点在线条与材质层次上，小尺寸直出会把这些糊掉；放大之后观感差别很大</li><li>不要搭配加速类 LoRA（Turbo / Lightning 之类）。训练用的底模是纯底模，加速 LoRA 的效果没有参与训练，叠加只会让画面过锐偏色</li></ul>AboutA single LoRA that captures the illustration style of a popular Pixiv artist. The look is a clean, flat cel-shaded anime style — crisp black lineart, flat fills with simple gradient shading, bright and airy colors, large simplified eyes, and petite proportions. Backgrounds are usually plain white or carry a decorative pattern (seigaiha waves, woven texture, and the like).This is my first attempt at training a style LoRA — and the first time I've used a human artist's work as the dataset rather than my own renders. Still rough in places; feedback is welcome.How to use it<ul><li>Base model: Anima base v1.0 — use the same base it was trained on, or the style will weaken</li><li>Start your prompt with <code>@fhbpn</code>. Recommended weight 0.8 – 1.2 (1.0 is closest to the original art; 1.2 gives stronger, bolder linework)</li><li>Sampling: 30 steps / CFG 3.5–4.5 / er_sde + simple</li><li>Use an upscale pass. The whole appeal of this style is in its linework and material detail, and a small direct generation flattens it out. Run SesquiLatentUpscale ×1.5, then a second pass at 10 steps with denoise 0.35 — the difference is substantial.</li><li>Do not stack accelerator LoRAs (Turbo, Lightning, etc.). Training ran on the plain base model, so their effect was never part of it; adding one on top only makes the image over-sharp and off-color.</li></ul>Training details265 public illustrations by the artist · resized to a 1536 long edge · WD14 auto-tagged with character names and style descriptors stripped out (so the trigger word owns the style) · dim 32 / alpha 16 / unet_lr 1e-4 / AdamW8bit / 3500 steps · final loss 0.0857.Known limitationsNight and low-light scenes are noticeably weak — the dataset contains almost no night illustrations, so those prompts tend to collapse into silhouettes. Bold extreme-perspective compositions aren't reproduced reliably either. And the closer you want to get to the source's level of detail, the more you depend on the upscale pass above.

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