For v0.0.0, I trained the LoRA using 24 training images featuring the same pose and the same room, plus 6 additional images showing variations of the pose and environment.As a result, applying the LoRA tends to overfit the pose and scenery, causing both to become strongly fixed.The training used the terms "virtual_insanity_pose" and "liminal space" in advance, but during generation, the model tends to reproduce the training images almost verbatim regardless of which trigger words are used.2:40～<div data-youtube-video><iframe width="640" height="480" allowfullscreen="true" autoplay="false" disablekbcontrols="false" enableiframeapi="false" endtime="0" ivloadpolicy="0" loop="false" modestbranding="false" origin playlist src="https://www.youtube.com/embed/QzfZuU_LPN0?si=Fc4L3ePgVTJlC2qP" start="0"></iframe></div>

Concept > Virtual insanity pose

Initial.dim8/alpha8, UNet LR 1e-04, AdamW8bit, warmup 0, constant 600 + cosine 400 steps(100/300steps), 512² reso, 26 images.

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