diff --git a/demo/realtime_model_inference_from_file.py b/demo/realtime_model_inference_from_file.py
index 1d56b07a..dbf24601 100644
--- a/demo/realtime_model_inference_from_file.py
+++ b/demo/realtime_model_inference_from_file.py
@@ -222,7 +222,7 @@ def main():
     target_device = args.device if args.device != "cpu" else "cpu"
     voice_sample = voice_mapper.get_voice_path(args.speaker_name)
     print(f"Using voice preset for {args.speaker_name}: {voice_sample}")
-    all_prefilled_outputs = torch.load(voice_sample, map_location=target_device, weights_only=False)
+    all_prefilled_outputs = torch.load(voice_sample, map_location=target_device, weights_only=True)
 
     # Prepare inputs for the model
     inputs = processor.process_input_with_cached_prompt(
diff --git a/demo/web/app.py b/demo/web/app.py
index 1b45117e..6165ce02 100644
--- a/demo/web/app.py
+++ b/demo/web/app.py
@@ -161,7 +161,7 @@ def _ensure_voice_cached(self, key: str) -> Tuple[object, Path, str]:
             prefilled_outputs = torch.load(
                 preset_path,
                 map_location=self._torch_device,
-                weights_only=False,
+                weights_only=True,
             )
             self._voice_cache[key] = prefilled_outputs