Update app.py

app.py

@@ -11,10 +11,10 @@ model_name = "unsloth/llama-3.2-1b-instruct-bnb-4bit"  # Base model
 adapter_name = "Alkhalaf/lora_model"  # LoRA model adapter
 
 # Load tokenizer
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=hf_token)
+tokenizer = AutoTokenizer.from_pretrained(model_name, token=hf_token)
 
 # Load the LoRA adapter configuration
-peft_config = PeftConfig.from_pretrained(adapter_name, use_auth_token=hf_token)
+peft_config = PeftConfig.from_pretrained(adapter_name, token=hf_token)
 
 # Load the base model
 base_model = AutoModelForCausalLM.from_pretrained(
@@ -26,7 +26,7 @@ base_model = AutoModelForCausalLM.from_pretrained(
     
 )
 # Apply the LoRA adapter to the base model
-model = PeftModel.from_pretrained(base_model, adapter_name, use_auth_token=hf_token)
+model = PeftModel.from_pretrained(base_model, adapter_name, token=hf_token)
 
 # Define prediction function
 def predict(input_text):