Update app.py

app.py

@@ -2,20 +2,17 @@ import gradio as gr
 from transformers import LlamaTokenizer, LlamaForCausalLM
 import torch
 
-# Load the fine-tuned model and tokenizer
-try:
-    tokenizer = LlamaTokenizer.from_pretrained("./fine_tuned_llama2")
-    model = LlamaForCausalLM.from_pretrained("./fine_tuned_llama2")
-    model.eval()
-    print("Model and tokenizer loaded successfully.")
-except Exception as e:
-    print(f"Error loading model or tokenizer: {e}")
-
 # Function to predict fraud based on text input
 def predict(input_text):
     if not input_text:
         return "Please enter some text to analyze."
+    
     try:
+        # Load the fine-tuned model and tokenizer inside the function
+        tokenizer = LlamaTokenizer.from_pretrained("./fine_tuned_llama2")
+        model = LlamaForCausalLM.from_pretrained("./fine_tuned_llama2")
+        model.eval()
+        
         # Tokenize input
         inputs = tokenizer(input_text, return_tensors="pt", max_length=512, padding="max_length", truncation=True)
         # Generate output