diff --git a/demo/inference_from_file.py b/demo/inference_from_file.py
index b26cfa5..a15aaf8 100644
--- a/demo/inference_from_file.py
+++ b/demo/inference_from_file.py
@@ -1,6 +1,7 @@
 import argparse
 import os
 import re
+import traceback
 from typing import List, Tuple, Union, Dict, Any
 import time
 import torch
@@ -175,11 +176,6 @@ def parse_args():
         default=1.3,
         help="CFG (Classifier-Free Guidance) scale for generation (default: 1.3)",
     )
-    parser.add_argument(
-        "--use_sdpa",
-        action="store_true",
-        help="Use sdpa attention mode instead of flash_attention_2",
-    )
     
     return parser.parse_args()
 
@@ -249,13 +245,23 @@ def main():
     processor = VibeVoiceProcessor.from_pretrained(args.model_path)
 
     # Load model
-    attn_implementation = "flash_attention_2" if not args.use_sdpa else "sdpa"
-    model = VibeVoiceForConditionalGenerationInference.from_pretrained(
-        args.model_path,
-        torch_dtype=torch.bfloat16,
-        device_map='cuda',
-        attn_implementation=attn_implementation # flash_attention_2 is recommended
-    )
+    try:
+        model = VibeVoiceForConditionalGenerationInference.from_pretrained(
+            args.model_path,
+            torch_dtype=torch.bfloat16,
+            device_map='cuda',
+            attn_implementation='flash_attention_2' # flash_attention_2 is recommended
+        )
+    except Exception as e:
+        print(f"[ERROR] : {type(e).__name__}: {e}")
+        print(traceback.format_exc())
+        print("Error loading model, try sdpa.")
+        model = VibeVoiceForConditionalGenerationInference.from_pretrained(
+            args.model_path,
+            torch_dtype=torch.bfloat16,
+            device_map='cuda',
+            attn_implementation='sdpa'
+        )
 
     model.eval()
     model.set_ddpm_inference_steps(num_steps=10)