Update description again

app.py

@@ -61,11 +61,12 @@ outputs = [gr.inputs.Image(type='pil', label="Output Image"), "highlight"]
 
 
 description = """A demonstration based on the Generic Attention-model Explainability method for Interpreting Bi-Modal
-                 Transformers by Chefer et al. (2021): https://github.com/hila-chefer/Transformer-MM-Explainability. \n \n
+                 Transformers by Chefer et al. (2021): https://github.com/hila-chefer/Transformer-MM-Explainability.
+
                  This demo shows attributions scores on both the image and the text input when presented CLIP with a
                  <text,image> pair. Attributions are computed as Gradient-weighted Attention Rollout (Chefer et al.,
                  2021), and can be thought of as an estimate of the effective attention CLIP pays to its input when
-                 computing a multimodal representation"""
+                 computing a multimodal representation."""
 
 iface = gr.Interface(fn=run_demo,
                      inputs=inputs,