a distillation lora for anima, trained on ~100 images at 1024x generated by the model itself using 40 steps cfg = 4 er_sde from diverse captions
baked-in negative prompt: worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia

may or may not be underbaked/overbaked
works best with cfg = 1 and 8 steps for heun/2s samplers, 16 steps for 1s or multistep samplers
the training code is a modification of diffusion-pipe for RL/distillation + custom comfyui nodes for data generation
TODO: get a larger more diverse RL dataset and filter it for artifacts