Update app.py

app.py

@@ -9,8 +9,8 @@ model = AutoModelForSeq2SeqLM.from_pretrained("hrshtsharma2012/NL2SQL-Picard-fin
 # Initialize the pipeline
 nl2sql_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
-# Load a part of the Spider dataset
-spider_dataset = load_dataset("spider", split='train[:5]')
+# Load a part of the WikiSQL dataset
+wikisql_dataset = load_dataset("wikisql", split='train[:5]')
 
 def generate_sql(query):
     results = nl2sql_pipeline(query)
@@ -19,8 +19,8 @@ def generate_sql(query):
     sql_query = sql_query.replace('<pad>', '').replace('</s>', '').strip()
     return sql_query
 
-# Use examples from the Spider dataset
-example_questions = [(question['question'],) for question in spider_dataset]
+# Use examples from the WikiSQL dataset
+example_questions = [(question['question'],) for question in wikisql_dataset]
 
 # Create a Gradio interface
 interface = gr.Interface(
@@ -29,7 +29,7 @@ interface = gr.Interface(
     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 WikiSQL dataset. Try one of the example questions or enter your own!"
 )
 
 # Launch the app