Gallery instead of Examples & Applications

app.py

@@ -11,7 +11,7 @@ PAGES = {
     "Text to Image": text2image,
     "Image to Text": image2text,
     "Localization": localization,
-    "Examples & Applications": examples,
+    "Gallery": examples,
 }
 
 st.sidebar.title("Explore our CLIP-Italian demo")

examples.py

@@ -3,7 +3,7 @@ import streamlit as st
 
 
 def app():
-    st.title("Examples & Applications")
+    st.title("Gallery")
     st.write(
         """
         
@@ -81,7 +81,7 @@ def app():
     col2.markdown("*A rustic chair*")
     col2.image("static/img/examples/sedia_rustica.jpeg", use_column_width=True)
 
-    st.markdown('## Localization')
+    st.markdown("## Localization")
 
     st.subheader("Un gatto")
     st.markdown("*A cat*")

introduction.md

@@ -37,7 +37,7 @@ to find where "something" (like a "cat") is an image. The location of the object
 
 <img src="https://huggingface.co/spaces/clip-italian/clip-italian-demo/raw/main/static/img/gatto_cane.png" alt="drawing" width="95%"/>
 
-+ **Examples & Applications**: This page showcases some interesting results we got from the model, we believe that there are 
++ **Gallery**: This page showcases some interesting results we got from the model, we believe that there are 
 different applications that can start from here.
 
 # Novel Contributions
@@ -256,7 +256,7 @@ labels most probably had an impact on the final scores.
 
 We hereby show some interesting properties of the model. One is its ability to detect colors, 
 then there is its (partial) counting ability and finally the ability of understanding more complex queries. You can find
-more examples in the "*Examples & Applications*" section of this demo.
+more examples in the "*Gallery*" section of this demo.
 
 To our own surprise, many of the answers the model gives make a lot of sense! Note that the model, in this case,
 is searching the right image from a set of 25K images from an Unsplash dataset.