Update README.md

README.md

@@ -14,7 +14,7 @@ This graft uses Krea2 turbo as an attention block donor that is blended on to Zi
 python graft_krea_to_zimage.py --krea-donor "...10Krea-turbo.safetensors" (just krea2 turbo with the TE defeaters merged in) --zimage-base "...z_image_turbo_bf16.safetensors" --output "krea2z_test10.safetensors" --target main --blocks 0:30 --strength 1.0 --kv --kv-strength 0.25 --mode linear-mag --orthogonal --remap shift --donor-shift 0 --out-proj --out-proj-strength 1.0 --mlp --mlp-strength 0.2 --include-gate --hidden-reduce svd --source-head-selection all48 --target-head-selection all --device cuda
 
 
-If you want to tinker with merging a different krea2 model to Zimage, none of these apply universally and are models specific: MLP strength will harm the zimage distillation and has a negative impact. High k/v will unwind tokenization somewhat and prompt response feels less accurate. Strength can go past 1.0 as well, 2.0 may work even. It is not easy to mess with these and write 12g models just to do one image and have it screwed up. But as far as my grafting has gone this is by far the easiest. Also, to be honest. This is THE best Zimage model hands down, just saying. If it works with LoRa's, not sure.
+If you want to tinker with merging a different krea2 model to Zimage, none of these apply universally and are models specific: MLP strength will harm the zimage distillation and has a negative impact. High k/v will unwind tokenization somewhat and prompt response feels less accurate. Strength can go past 1.0 as well, 2.0 may work even. It is not easy to mess with these and write 12g models just to do one image and have it screwed up. But as far as my grafting has gone this is by far the easiest. This has greater impacts on a multimodal video model like H3 in which attention layers control audio, next frame motion, and composition all at once which is much harder to graft to.
 
 
 Also, all of the above is my own wording. I'm not an ML guy I'm a results-oriented producer and a creative. Any Machine Learning undergraduates that read this, please go ahead and take this as your thesis, I'm done explaining it. Here is my coding partner's write-up: