Update app.py

app.py

@@ -6,14 +6,14 @@ from datasets import load_dataset
 tokenizer = T5Tokenizer.from_pretrained('t5-small', legacy=False)
 model = T5ForConditionalGeneration.from_pretrained('t5-small')
 
-dataset = load_dataset("b-mc2/sql-create-context", split='train')
+dataset = load_dataset("b-mc2/sql-create-context")
 
-examples = []
+# examples = []
 
-for i in range(3):  # Let's take the first 3 examples
-    item = dataset[i]
-    question = item['question']
-    examples.append([question])
+# for i in range(3):  # Let's take the first 3 examples
+#     item = dataset[i]
+#     question = item['question']
+#     examples.append([question])
 
 def generate_sql(question):
     # Format the question for the model if needed. For example:
@@ -38,7 +38,7 @@ iface = gr.Interface(
     outputs=gr.Textbox(),
     title="Natural Language to SQL",
     description="This app uses a Seq2Seq model to generate SQL queries from natural language questions.",
-    examples=examples
+    # examples=examples
 )
 
 # Launch the app