Faye is trained from 100% generated images! Any likeness to person(s) living or dead is as coincidental as finding your own doppelganger out there - could happen, not intentional. Her reference images were created using Krea 2, Flux 2 Klein, and Gemini. Then she was put through a bunch of tuning passes.She is done... Final is a purely re-trained version built from generating about 2,000 images to get proper proportions, angles, shape, and frame out of the multiple failed models - of which, I narrowed to 21 diverse photos to capture as much range as possible. I couldn't leave the problem unfinished. She is complete.Sick Ollie, Analogue Madness, and anything from Stable Yogi as a base model can drift her age young in some cases, just like her other attempts. The best I can attribute this to is hair, face, and neckline tapping into blocks that are of younger women - she meets the same metrics as Tegan and Carys (and they don't drift young in the same prompts).Likely will have small lapses of look, as I couldn't get EVERY image to be completely identical to character. Drift you see in the previews is mostly base-model drift (I have tested her in 12 different base models and she mostly carries her look throughout). <hr />For context, I now have about 10 different scripts to extract spatial, textural, and compositional data about characters, 8 different compression and pruning scripts, and 6 re-weighting and mergine/combination scripts. You can't easily fix a poorly trained model! Your work is best suited for building CLEAN and SOLID training data! These tools will (and have already) helped build out more generic LoRA for you all. I hope to release some of them as I get them more broadly tested.

Faye

Faye has been completely retrained. I rebuilt her core dataset, meticulously, cautiously.

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