Update README.md

README.md

@@ -33,13 +33,13 @@ Overall, model performs particularly well with textures and patterns that were p
 
 ![unified_characters_standalone](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/9RIxkWpmT9j_z2uGOWIXa.png)
 
-This benchmark measures character similarity across 1815 characters in this iteration of it.
+This benchmark measures character similarity across 1815 characters in this iteration of it. For convenience, we've gathered few major categories: gachas and vtubers.
 
-We utilize reference(non-generated) set of images, and measure character features against ai-generated data - this is the similarity score. Our custom in-house model for character discrimination trained on ~1.2kk images is used.
+We utilize reference(non-generated) set of images, and measure character features against ai-generated data - this is the similarity score. Our custom in-house model for character discrimination trained on ~1.2kk images is used. Results are sorted indiscriminately, by score, treat it as general character knowledge index, not as any specific characters in particular. Same point on graphs might, or might not be corresponding to the same character.
 
-Due to compute constraint, we selected only single model to compare against - not yet released latest version of [Chenkin](https://huggingface.co/ChenkinNoob/ChenkinNoob-XL-V0.3-BETA) model, which is the most trained SDXL-based anime model currently.
+Due to compute constraint, we selected only single model to compare against - not yet released latest version of [Chenkin](https://huggingface.co/ChenkinNoob/ChenkinNoob-XL-V0.3-BETA) model, which currently is the most trained SDXL-based anime model.
 
-Fuure benchmark iterations might include different arches and more models.
+Future benchmark iterations might include different arches, more models and more characters.
 
 ## Bias and Limitations
 
@@ -65,7 +65,7 @@ Flux 2 VAE seem to have brown bias overall, which can be alleviated by adding `s
 We will provide a Node, and hope it will be adapted natively in main repo eventually:  
 **https://github.com/Anzhc/SDXL-Flux2VAE-ComfyUI-Node**
 
-Just install it, and it will patch the model config, no mode changes required.
+Just install it, and it will patch the model config, no node changes required.
 
 
 Apparently works in [SwarmUI](https://github.com/mcmonkeyprojects/SwarmUI) as is.
@@ -87,25 +87,24 @@ Recommended Parameters:
 
 #### A1111 WebUI
 
-(All screenshots are repeating our RF release, as there is no difference in setup)
-
 
 Recommended WebUI: [ReForge](https://github.com/Panchovix/stable-diffusion-webui-reForge) - has native support for Flow models, and we've PR'd our native support for Flux2vae-based SDXL modification.
 
 
 **How to use in ReForge**:
 
-![изображение](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/UV5Yp66H7YlccdQqborPf.png)
-(ignore Sigma max field at the top, this is not used in RF)
+![изображение](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/5H8vNl7ZzUh8F_4japzV9.png)
 
 Support for RF in ReForge is being implemented through a built-in extension:
 
-![изображение](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/LpMF0lmC96X001Au9fFU_.png)
+![изображение](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/Oo1_7dD2Lv7BRqeV_pUsg.png)
+
+**IMPORTANT**
 
+Set your preview method to this, if you use it.
 
 ![imagen](https://cdn-uploads.huggingface.co/production/uploads/634cf025fe861cc73a2e7dd0/siEBfX41E6D_DUEqaXMgs.png)
 
-Set parameters to that, and you're good to go.
 
 Flux2VAE does not currently have an appropriate high quality preview method, please use Approx Cheap option, which would allow you to see simple PCA projection(ReForge).