V2.5 for ZIT is trained on base and plays along well with other loras on ZIT. Improvement focused on accurate female genitalia.Added version trained on Z-Image "Base". All samples are genned on Z-Image Turbo, where the main benefit is that it seems much more resilient on stacking loras and has less of an effect on overwriting features or look from other loras.Added version trained on ZIT, the effect is pretty subdued but cuts away from the cinematic color with very little impact on detail on my tests, also steer models preference bit away from asian women. Works without trigger phrase, but was trained with "Low quality cellphone photo of". For accurate representation of genitals, look for some other lora.Added WAN 2.2 T2V models, trained on the same dataset as V1. All gens done with Lightning 4 steps loras @480p, so likely there's possibility of improved quality by improving the workflow.V1.5 is more consistent and degrades Flux quality less, but the nude selfie might not be as authentic or perform as good as V1.0. Art nude dataset was added and nude selfie dataset was expanded considerably.Flux lora trained on non-specific set of 50 or so images of amateur nudes, mostly selfies and mirror selfies. Knows "nude selfie" and to lesser degree breast sizes and body shapes, prompt following for body sizes is limited but it's definitely not as stuck on the model body as base Flux.Anatomy is not perfect by any means.

Amateur nudes - FLUX, Wan 2.2, ZIT, (ZIB)

amateurnudes_captions.safetensors

v1.0 - Flux

v2.5 Z-Image Turbo

Files with SHA256: 285475c8136185f83e9d70310e65aa24d4650a28af3af9e5118cadf01c5ea2d4