Update app.py

app.py

@@ -164,15 +164,15 @@ def inference(image, upscale, large_input_flag, color_fix):
 
 
 
-title = "SAFMN for Real-world SR"
+title = "SAFMN for Real-world SR (running on CPU)"
 description = ''' ### Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution - ICCV 2023
 #### [Long Sun](https://github.com/sunny2109), [Jiangxin Dong](https://scholar.google.com/citations?user=ruebFVEAAAAJ&hl=zh-CN&oi=ao), [Jinhui Tang](https://scholar.google.com/citations?user=ByBLlEwAAAAJ&hl=zh-CN), and [Jinshan Pan](https://jspan.github.io/)
 #### [IMAG Lab](https://imag-njust.net/), Nanjing University of Science and Technology
 #### Drag the slider on the super-resolution image left and right to see the changes in the image details.
 #### SAFMN performs x2/x4 upscaling on the input image.  If the input image is larger than 720P, it is recommended to use Memory-efficient inference.
 <br>
-
-If our work is useful for your research, please consider citing:
+#### If our work is useful for your research, please consider citing:
+<br>
 <code>
 @inproceedings{sun2023safmn,
     title={Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution},