added examples

app.py

@@ -14,11 +14,20 @@ def classify_text(plot):
     predictions = pipe(plot)[0]
     return {label_map[pred['label']]: float(pred['score']) for pred in predictions}
 
+examples = [
+            ["My frying pan dried with a spot that looks like a pig"], 
+            ["Adult peer pressure is hearing your neighbor mowing so you decide you better mow too"],
+            ['a bear walks into a bar and says, "give me a whiskey and... cola"'],
+            ["Worst Celebrity Private Jet CO2 Emissions Offenders (2022)"],
+            ["Billionaire No More: Patagonia Founder Gives Away the Company - Profits will now go towards climate action"],
+            ]
+
 iface = gr.Interface(
     description = "Enter a title for a reddit post, and the model will attempt to predict the subreddit.",
     article = "<p style='text-align: center'><a href='https://github.com/daspartho/predict-subreddit' target='_blank'>Github</a></p>",
     fn=classify_text, 
     inputs=gr.inputs.Textbox(label="Type the title here"), 
     outputs=gr.outputs.Label(label='What the model thinks'),
+    examples=examples
     )
 iface.launch()