Upload convert_to_state.py

convert_to_state.py

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+import torch
+from torchvision import models
+
+# Step 1: create the model architecture
+model = models.efficientnet_b0(pretrained=False)
+model.classifier[1] = torch.nn.Linear(model.classifier[1].in_features, 2)
+
+# Step 2: load your previous checkpoint
+state_dict = torch.load("models/efficientnet_b0_ffpp_c23.pth", map_location="cpu")
+model.load_state_dict(state_dict, strict=False)
+
+# Step 3: save only the weights
+torch.save(model.state_dict(), "models/deeptrust_weights.pt")
+print("Saved state_dict as models/deeptrust_weights.pt")