added example

app.py

@@ -11,11 +11,11 @@ def classify(img):
     pred,idx,probs=learn.predict(img)
     return dict(zip(categories, map(float,probs)))
 
-
+examples=['This was a very though provoking movie and very well written']
 title = "Text sentiment classifier"
 description = "This model classifies a sentence of text as having a positive or negative setiment"
 text = gr.Textbox()
 label= gr.Label()
 
-intf=gr.Interface(fn=classify,inputs=text,outputs=label,title=title, description=description)
+intf=gr.Interface(fn=classify,inputs=text,outputs=label,title=title, description=description, examples=examples)
 intf.launch(inline=False)