Because of my lack of experience and time, the version number may be based on changes that have made certain aspects worse. As such a previous version may perform better than a later version.

I'm still learning the ins and outs of the model and LoRA training in general, please leave reproducible feedback or tips so that I may improve over time.

Check the "About this version" section for any quirks or pitfalls I'm aware of, this is trained with a small dataset and so it is expected to have more bias

Some Q's:

What's your workflow?
- Sampler from images is done with Restarts with segments of [3,2,0.06,0.30], which are values from the paper on Restarts
- Initial resolution is typically 768 x 1152 or vice-versa and upscaled by x(5/3), I try to keep the pixel count around 1024 x 1024 for initial gens and adjust the upscale ratio as needed
- Upscaler is usually 4x_fatal_Anime_500000_G or 4x_NMKD-Siax_200k
- Second sample pass is the same as the first (params are on civit's meta interface) but at ~.35 denoise
- A facedetailer is used
- I use ComfyUI, sorry
What strength should I be using?
- 1