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

[Anima] Flash 8 steps cfg 1 distilled

epoch 50 on 100 images, continued from epoch 15 but with grad accum 2

Files with SHA256: 323d8ee331b4ae67b1d1b9029cadfadbdc3b164bdf506e860f22ff54a5e4a962