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model.py

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+import torch
+import torch.nn as nn
+
+class MNISTModel(nn.Module):
+    def __init__(self):
+        super(MNISTModel, self).__init__()
+        self.fc1 = nn.Linear(28 * 28, 128)  # MNIST images are 28x28
+        self.fc2 = nn.Linear(128, 10)
+        self.dropout = nn.Dropout(0.5)
+
+    def forward(self, x):
+        x = x.view(-1, 28 * 28)  # Flatten the input
+        x = torch.relu(self.fc1(x))
+        x = self.dropout(x)
+        x = self.fc2(x)
+        return x