Update app.py

app.py

@@ -6,16 +6,13 @@ from datasets import load_dataset
 tokenizer = AutoTokenizer.from_pretrained("hrshtsharma2012/NL2SQL-Picard-final")
 model = AutoModelForSeq2SeqLM.from_pretrained("hrshtsharma2012/NL2SQL-Picard-final")
 
-# 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]')
 
 def generate_sql(query):
-    results = nl2sql_pipeline(query)
-    # Ensure that we get the first generated text as the SQL query
-    sql_query = results[0]['generated_text'] if results else "No SQL query generated"
+    input_ids = tokenizer(query, return_tensors="pt").input_ids
+    outputs = model.generate(input_ids)
+    sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return sql_query
 
 # Use examples from the Spider dataset
@@ -28,7 +25,7 @@ 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 Spider dataset. Try  example questions or enter your own!"
 )
 
 # Launch the app