added documentation as markdown and rounded score

app.py

@@ -34,7 +34,7 @@ embedding_input_topic = model.encode(input_topic)
 
 cos_scores = util.cos_sim(embedding_input_topic, embedding_sentence)[0][0]
 
-st.write('Score for topic', input_topic, ':', cos_scores.tolist())
+st.write('Score for topic', input_topic, ':', np.round(cos_scores.tolist(),2))
 
 l_scores = []
 for topic in ['Space','Transportation','Health']:
@@ -44,7 +44,8 @@ for topic in ['Space','Transportation','Health']:
 
 st.write('Most likely topic:', ['Space','Transportation','Health'][np.argmax(l_scores)])
 
-st.markdown('## ')
+st.markdown('##  Adding bulk sentences and topics')
+st.markdown('In this section we can upload a file with sentences (one column, header "sentence") and a file with topics (one column, header "topics") we can compute the most likely topic')
 uploaded_file1 = st.file_uploader("Choose a file: sentence list")
 if uploaded_file1 is not None:
     #read csv