Update app.py

app.py

@@ -117,7 +117,7 @@ image_2 = gr.inputs.Image(type="filepath")
 text_1 = gr.inputs.Textbox(lines=5)
 text_2 = gr.inputs.Textbox(lines=5)
 
-examples = [['examples/image_1.png', 'examples/text_1.txt', 'examples/image_2.jpg', 'examples/text_2.txt']]
+examples = [['examples/image_1.png', '#IndiaFightsCorona:\n\nNearly 4.5 million beneficiaries vaccinated against #COVID19 in 19 days.\n\nIndia is the fastest country to cross landmark of vaccinating 4 million beneficiaries in merely 18 days.\n\n#StaySafe #IndiaWillWin #Unite2FightCorona https://t.co/beGDQfd06S', 'examples/image_2.jpg', '#IndiaFightsCorona:\n\nIndia has become the fastest nation to reach 4 million #COVID19 vaccinations ; it took only 18 days to administer the first 4 million #vaccines\n\n:@MoHFW_INDIA Secretary\n\n#StaySafe #IndiaWillWin #Unite2FightCorona https://t.co/9GENQlqtn3']]
 
 label = gr.outputs.Label()
 
@@ -125,7 +125,7 @@ iface = gr.Interface(classify_info,
 	inputs=[image_1, text_1, image_2, text_2], outputs=label,
 	examples = examples,
 	title="Multimodal Entailment Keras",
-	description = "Model for classifying whether image and text from one scenario complements the image and text from another scenario. They can be contradictory, implied or no entailment",
+	description = "Model for classifying whether image and text from one scenario complements the image and text from another scenario. They can be contradictory, implied or no entailment. Example images and text from the dataset in raw form !",
         article = "Author: <a href=\"https://huggingface.co/reichenbach\">Rishav Chandra Varma</a>")
 
 iface.launch()