Update app.py

app.py

@@ -47,8 +47,9 @@ def classify_compliant(text):
 #build the Gradio app
 #Instructuction = "Write an imaginary review about a product or service you might be interested in."
 title="Customer Complaints Categorization"
-description = """This application uses fine-tune BERT to perform Customer Complaints Categorization.BERT models are usually pretrained on a large corpus of text and then fine tuned for specific tasks.
+description = """This application uses fine-tune BERT to perform Customer Complaints Categorization. BERT models are usually pretrained on a large corpus of text and then fine tuned for specific tasks.
 Effectively handling customer complaints provides an opportunity for the service provider to resolve the customer’s problems on time and thus reduce dissatisfaction levels.
+
 Write a complaint on an insurance product or service and see how the machine learning model is able to Categorisation your Complaint.
 The Complaints Type are:
 1. Debt Collection 
@@ -64,7 +65,7 @@ article = """
            """
 
 demo = gr.Interface(classify_compliant,
-            inputs=gr.Textbox(lines =10,label = "Type your Complaint of our Product here or for a quick demo click on the examples provided below and output will automatically be populatec in the output box ", max_lines = 20),
+            inputs=gr.Textbox(lines =10,label = "Type your Complaint of our Product here or for a quick demo click on the examples provided below and output will automatically be populated in the output box ", max_lines = 20),
             outputs = gr.Textbox(lines =5,label = "Complaint Category"),
             title = title,
             description = description,