Update app.py

app.py

@@ -25,16 +25,7 @@ pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
 def text_to_sql(text):
     # Load Model with PEFT adapter
-    model = AutoModelForCausalLM.from_pretrained(
-        "jinhybr/code-llama-7b-text-to-sql",
-        device="cuda" if torch.cuda.is_available() else "cpu",
-        torch_dtype=torch.float16
-    )
-    tokenizer = AutoTokenizer.from_pretrained("jinhybr/code-llama-7b-text-to-sql")
-
-    # load into pipeline
-    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
+    
     # Define schema and user question
     #schema = "CREATE TABLE table_17429402_7 (school VARCHAR, last_occ_championship VARCHAR)"
     schema = 'You are an text to SQL query translator. Users will ask you questions in English and you will generate a SQL query based on the provided SCHEMA.\nSCHEMA:\nCREATE TABLE table_17429402_7 (school VARCHAR, last_occ_championship VARCHAR)'