Update README.md

README.md

@@ -275,16 +275,15 @@ extra_gated_fields:
   "I acknowledge the license agreement stated above and pledge to utilize the Software strictly for non-commercial research": checkbox
 
 ---
-[![Download](https://img.shields.io/badge/-Download%20Model-brightgreen?style=for-the-badge&logo=appveyor)](https://huggingface.co/FFusion/FFusionXL-09-SDXL/blob/main/FFusionXL-09-SDXL.safetensors)
 
 # FFXL Model Card
 <div style="display: flex; flex-wrap: wrap; gap: 2px;">
   <img src="https://img.shields.io/badge/%F0%9F%94%A5%20Refiner%20Compatible-Yes-success">
   <img src="https://img.shields.io/badge/%F0%9F%92%BB%20CLIP--ViT%2FG%20and%20CLIP--ViT%2FL%20tested-Yes-success">
+  <img src="https://img.shields.io/badge/%F0%9F%A7%A8%20FFXL%20Diffusers-available-brightgreen">
 </div>
 
-
-![FFusionAI_00187_.png](https://cdn-uploads.huggingface.co/production/uploads/6380cf05f496d57325c12194/dtRkHom_cxGSzCV2ReeVc.png)
+![ffusionXL.jpg](https://cdn-uploads.huggingface.co/production/uploads/6380cf05f496d57325c12194/iM_2uykpHRQsZgLvIjJJl.jpeg)
 
 ## Model
 
@@ -293,7 +292,7 @@ First, we use a base model to generate latents of the desired output size.
 In the second step, we use a specialized high-resolution model and apply a technique called SDEdit (https://arxiv.org/abs/2108.01073, also known as "img2img") 
 to the latents generated in the first step, using the same prompt.
 
-[![Download](https://img.shields.io/badge/-Download%20Model-brightgreen?style=for-the-badge&logo=appveyor)](https://huggingface.co/FFusion/FFusionXL-LoRa-SDXL-Potion-Art-Engine/resolve/main/FFusionXL-LoRa-SDXL-Potion-Art-Engine.safetensors)
+[![Download](https://img.shields.io/badge/-Download%20Model-brightgreen?style=for-the-badge&logo=appveyor)](https://huggingface.co/FFusion/FFusionXL-09-SDXL/blob/main/FFusionXL-09-SDXL.safetensors)
 
 
 ### Model Description
@@ -304,6 +303,8 @@ to the latents generated in the first step, using the same prompt.
 - **Model Description:** This is a trained model based on SDXL that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses two fixed, pretrained text encoders ([OpenCLIP-ViT/G](https://github.com/mlfoundations/open_clip) and [CLIP-ViT/L](https://github.com/openai/CLIP/tree/main)).
 - **Resources for more information:**  [SDXL paper on arXiv](https://arxiv.org/abs/2307.01952).
 
+![FFusionAI_00187_.png](https://cdn-uploads.huggingface.co/production/uploads/6380cf05f496d57325c12194/dtRkHom_cxGSzCV2ReeVc.png)
+
 ### Model Sources
 
 - **Demo:** soon
@@ -317,7 +318,7 @@ to the latents generated in the first step, using the same prompt.
 
 
 ### 🧨 Diffusers 
-![ffusionXL.jpg](https://cdn-uploads.huggingface.co/production/uploads/6380cf05f496d57325c12194/iM_2uykpHRQsZgLvIjJJl.jpeg)
+
 Make sure to upgrade diffusers to >= 0.18.0:
 ```
 pip install diffusers --upgrade