Update app.py

app.py

@@ -6,6 +6,7 @@ from datasets import load_dataset
 tokenizer = T5Tokenizer.from_pretrained('t5-small')
 model = T5ForConditionalGeneration.from_pretrained('t5-small')
 
+dataset = load_dataset("wikisql", split='test')[:3]
 def generate_sql(question):
     # Format the question for the model if needed. For example:
     # input_text = f"translate English to SQL: {question}"
@@ -21,13 +22,16 @@ def generate_sql(question):
     sql_query = tokenizer.decode(output_ids, skip_special_tokens=True)
     return sql_query
 
+examples = [[item['question']] for item in dataset]
+    
 # Define the Gradio interface
 iface = gr.Interface(
     fn=generate_sql,
     inputs=gr.Textbox(lines=2, placeholder="Enter your question here..."),
     outputs=gr.Textbox(),
     title="Natural Language to SQL",
-    description="This app uses a Seq2Seq model to generate SQL queries from natural language questions."
+    description="This app uses a Seq2Seq model to generate SQL queries from natural language questions.",
+    examples=examples
 )
 
 # Launch the app