Update README.md

README.md

@@ -19,11 +19,6 @@ Use the tokens **_redshift style_** in your prompts for the effect.
 **If you enjoy my work and want to test new models before release, please consider supporting me**
 [![Become A Patreon](https://badgen.net/badge/become/a%20patron/F96854)](https://patreon.com/user?u=79196446)
 
-# Gradio
-
-We support a [Gradio](https://github.com/gradio-app/gradio) Web UI run redshift-diffusion:
-[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/nitrosocke/Redshift-Diffusion-Demo)
-
 **Characters rendered with the model:**
 ![Videogame Samples](https://huggingface.co/nitrosocke/redshift-diffusion/resolve/main/images/redshift-diffusion-samples-01s.jpg)
 **Cars and Landscapes rendered with the model:**
@@ -37,6 +32,13 @@ _Steps: 40, Sampler: DPM2 Karras, CFG scale: 7, Seed: 908018284, Size: 512x704_
 **redshift style Ford Mustang**
 _Steps: 20, Sampler: DPM2 Karras, CFG scale: 7, Seed: 579593863, Size: 704x512_
 
+This model was trained using the diffusers based dreambooth training by ShivamShrirao using prior-preservation loss and the _train-text-encoder_ flag in 11.000 steps.
+
+### Gradio
+
+We support a [Gradio](https://github.com/gradio-app/gradio) Web UI run redshift-diffusion:
+[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/nitrosocke/Redshift-Diffusion-Demo)
+
 ### 🧨 Diffusers
 
 This model can be used just like any other Stable Diffusion model. For more information,
@@ -58,8 +60,6 @@ image = pipe(prompt).images[0]
 image.save("./magical_princess.png")
 ```
 
-This model was trained using the diffusers based dreambooth training by ShivamShrirao using prior-preservation loss and the _train-text-encoder_ flag in 11.000 steps.
-
 ## License
 
 This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.