Upload 2 files

app.py

@@ -59,6 +59,6 @@ demo = gr.Interface(
 )
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch(share=False)
 else:
-    app = demo.launch(share=True)
+    app = demo.launch(share=False)

model_utils.py

@@ -111,9 +111,16 @@ class GPT(nn.Module):
 def load_model(model_path):
     """Load the trained model"""
     try:
-        torch.serialization.add_safe_globals({'GPTConfig': GPTConfig})
-        checkpoint = torch.load(model_path, map_location=torch.device('cuda' if torch.cuda.is_available() else 'cpu'), weights_only=True)
-        config = GPTConfig(**checkpoint['config'])
+        checkpoint = torch.load(model_path, map_location=torch.device('cuda' if torch.cuda.is_available() else 'cpu'))
+        
+        # Create config from the saved dictionary
+        config_dict = checkpoint['config']
+        if isinstance(config_dict, str):
+            # If config was saved as string, parse it to dict
+            import ast
+            config_dict = ast.literal_eval(config_dict)
+        config = GPTConfig(**config_dict)
+        
         model = GPT(config)
         model.load_state_dict(checkpoint['model_state_dict'])
         model.eval()