Update app.py

app.py

@@ -6,9 +6,6 @@ from datasets import load_dataset
 tokenizer = AutoTokenizer.from_pretrained("hrshtsharma2012/NL2SQL-Picard-final")
 model = AutoModelForSeq2SeqLM.from_pretrained("hrshtsharma2012/NL2SQL-Picard-final")
 
-# Load a part of the Spider dataset
-spider_dataset = load_dataset("spider", split='train[:5]')
-
 def generate_sql(query):
     input_text = "translate English to SQL: " + query
     inputs = tokenizer(input_text, return_tensors="pt", padding=True)
@@ -16,17 +13,13 @@ def generate_sql(query):
     sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return sql_query
 
-# Use examples from the Spider dataset
-example_questions = [(question['question'],) for question in spider_dataset]
-
 # Create a Gradio interface
 interface = gr.Interface(
     fn=generate_sql,
     inputs=gr.Textbox(lines=2, placeholder="Enter your natural language query here..."),
     outputs="text",
-    examples=example_questions,
     title="NL to SQL with Picard",
-    description="This model converts natural language queries into SQL using the Spider dataset. Try one of the example questions or enter your own!"
+    description="This model converts natural language queries into SQL using the Spider dataset. Enter your query!"
 )
 
 # Launch the app