<h3 id="suggested-trigger-words:-mqqet5nib">Suggested Trigger Words:</h3>A trigger word activates your LoRA’s effect during generation. You can use a mix of general and unique keywords:<ul><li>General: <code>"flux_3d_render"</code>, <code>"cyber_3d_glow"</code>, <code>"detailed_skirt_flux"</code></li><li>More Specific: <code>"flux_fashion_3d"</code>, <code>"cyberillustrious_glow"</code>, <code>"flux_cyberpunk_clothing"</code></li><li>Extra Keywords (to enhance the effect): <code>"glowing accents"</code>, <code>"detailed fabric"</code>, <code>"neon lighting"</code>, <code>"realistic anime 3D shading"</code></li></ul><hr /><h3 id="3.-minimum-training-parameters-for-best-results:-vvjdmx1da">3. Minimum Training Parameters for Best Results:</h3>If you trained using Flux, here’s a recommended baseline for LoRA training parameters:Dataset &amp; Preprocessing:<ul><li>Image Size: <code>1024x1024</code> (higher for better detail, but depends on VRAM)</li><li>Dataset Type: <code>Anime 3D render, cyberpunk, fashion-focused images</code></li><li>Training Images: <code>100–300 high-quality images (with variation in poses, skirts, glowing effects, etc.)</code></li><li>Captioning: Use <code>"detailed_skirt"</code>, <code>"glowing_effects"</code>, <code>"cyberpunk_fashion"</code>, etc., in metadata</li></ul>Training Settings:<ul><li>Network Rank: <code>32–64</code> (higher values improve detail, but require more VRAM)</li><li>Alpha: <code>16</code> (for good generalization without overfitting)</li><li>Batch Size: <code>4–8</code></li><li>Epochs: <code>5–10</code> (or monitor loss for best stopping point)</li><li>Learning Rate: <code>1e-4</code> (fine-tune based on loss function)</li></ul>

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