Minor formatting

app.py

@@ -48,9 +48,9 @@ st.markdown("This demo uses the sentence_transformers library to plot sentence s
 # Streamlit text boxes
 text = st.text_area('Enter sentences:', value="The sun is hotter than the moon.\nThe sun is very bright.\nI hear that the universe is very large.\nToday is Tuesday.")
 
-nc = st.slider('Select a number of clusters', min_value=1, max_value=15, value=3)
+nc = st.slider('Select a number of clusters:', min_value=1, max_value=15, value=3)
 
-model_type = st.radio("Choose model", ('Sentence Transformer', 'Universal Sentence Encoder'), index=0)
+model_type = st.radio("Choose model:", ('Sentence Transformer', 'Universal Sentence Encoder'), index=0)
 
 # Model setup
 if model_type == "Sentence Transformer":
@@ -72,6 +72,7 @@ if text:
     for i,em in enumerate(embed):
         for j,ea in enumerate(embed):
             sim[i][j] = 1.0-cosine(em,ea)
+    st.subheader("Similarity Heatmap")
     plot_heatmap(sentences, sim)
     st.subheader("Results from K-Means Clustering")
     cluster_examples(sentences, embed, nc)