Update streamlit_app.py

streamlit_app.py

@@ -6,7 +6,7 @@ from transformers import pipeline
 st.title("News App - Created by Group 09")
 
 #creating the sub heading
-st.write("## Welcome! In this app users may find the below features")
+st.write("### Welcome! In this app users may find the below features")
 
 #creating the content included in the page
 st.write("The users can work with uploaded using the Classification page which includes")
@@ -22,8 +22,10 @@ st.write("""
 - Key-Word recognition 
 """)
 
-st.write(" ## In order to test the classification of the model quickly,")
+#creating a test
+st.write(" ### For a quick test to see how the model classifies,")
 
+#calling and loading the fine tuned model which is uploaded to the hugging face 
 @st.cache_resource
 def load_classifier():
     return pipeline(
@@ -32,11 +34,15 @@ def load_classifier():
         truncation=True
     )
 
+#calling the model which is now loaded in using a simple variable 
 classifier = load_classifier()
 
+#the user text
 user_text = st.text_area("Type a sentence below:")
 
+#running the user text through the model to get the output 
 if st.button("Classify Text"):
+    #if no proper text
     if not user_text.strip():
         st.warning("Please enter some text.")
     else:
@@ -44,7 +50,8 @@ if st.button("Classify Text"):
             result = classifier(user_text)
 
         st.success("Classification complete.")
-        st.write("### Prediction", result[0]["label"])
+        #giving the outputs 
+        st.write("#### Prediction", result[0]["label"])
 
         if "score" in result[0]:
-            st.write("### Confidence",round(result[0]["score"], 4))
+            st.write("#### Confidence",round(result[0]["score"], 4))