Update README.md

README.md

@@ -18,7 +18,7 @@ WORKFLOW:
 https://huggingface.co/LokkenJP/TenEros_Max_optimized_learned/tree/main/SampleWorkFlowTwoPassOptimized
 
 
-beta_7 is a more correct format for average usability and combination of all working strategies so far. The merge is combination of the best lora data avaliable, premerged and then converted into MLP-only versions that were merged with magnitude cap, leaving full base model attention and reference intact. Gate-side data only allows for full base model behavior with extra data only needed to be reach with correct prompts. The base is an fl2va model with the Fast Omni timestep, then refolded, allowing full hybridization and not the fake half-model kind of hybrid without a timestep. Does all modes with one key drawback being the need for VSA and 90% sparsity and some undiagnosed issues from the Omni structure; it is prone to 'flickering' in the background and on the latent in workflows with single pass and without refined sampling setups like 2-pass sampling. The 3D spatial upscale pass smooths the latent and removes it. The 8 step turbo covers 6-12 steps and is devoid of most turbo quality reductions aside from some more jagged noise, a tradeoff for letting v-band stay fully base to avoid contrast gains from turbo and preserve input quality, sampling on most normal setups, but for optimal quality Euler/Simple or Er_sde/SGM_uniform are reliable. 
+beta_7 is a more correct format for average usability and combination of all working strategies so far. The merge is combination of the best lora data avaliable, premerged and then converted into MLP-only versions that were merged with magnitude cap, leaving full base model attention and reference intact. Isolating the merge to Gate-side data in MLP only allows for full base model behavior with extra data only needed to be reach with correct prompts. Should H3 loras all be trained only in MLP, and at much lower ranks? Probably if you ask me. The base is an fl2va model with the Fast Omni timestep, then refolded, allowing full hybridization and not the fake half-model kind of hybrid without a timestep. Does all modes with one key drawback being the need for VSA and 90% sparsity and some undiagnosed issues from the Omni structure; it is prone to 'flickering' in the background and on the latent in workflows with single pass and without refined sampling setups like 2-pass sampling. The 3D spatial upscale pass smooths the latent and removes it. The 8 step turbo covers 6-12 steps and is devoid of most turbo quality reductions aside from some more jagged noise, a tradeoff for letting v-band stay fully base to avoid contrast gains from turbo and preserve input quality, sampling on most normal setups, but for optimal quality Euler/Simple or Er_sde/SGM_uniform are reliable.