Update pytorch-model.md with a new troubleshooting help

burn-book/src/import/pytorch-model.md

@@ -15,10 +15,10 @@ tutorial on importing a more complex model.
 ## How to export a PyTorch model
 
 If you have a PyTorch model that you want to import into Burn, you will need to export it first,
-unless you are using a pre-trained published model. To export a PyTorch model, you can use the
-`torch.save` function.
+unless you are using a pre-trained published model. To export a PyTorch model correctly, you need to
+save only the model weights (state_dict) using the `torch.save` function, not the entire model.
 
-The following is an example of how to export a PyTorch model:
+The following is an example of how to properly export a PyTorch model:
 
 ```python
 import torch
@@ -38,12 +38,24 @@ class Net(nn.Module):
 if __name__ == "__main__":
     torch.manual_seed(42)  # To make it reproducible
     model = Net().to(torch.device("cpu"))
-    model_weights = model.state_dict()
-    torch.save(model_weights, "conv2d.pt")
+    model_weights = model.state_dict()  # This extracts just the weights
+    torch.save(model_weights, "conv2d.pt")  # Save only the weights, not the entire model
 ```
 
-Use [Netron](https://github.com/lutzroeder/netron) to view the exported model. You should see
-something like this:
+If you accidentally save the entire model instead of just the weights, you may encounter errors
+during import like:
+
+```
+Failed to decode foobar: DeserializeError("Serde error: other error:
+Missing source values for the 'foo1' field of type 'BarRecordItem'.
+Please verify the source data and ensure the field name is correct")
+```
+
+You can verify if your model is exported correctly by opening the `.pt` file in
+[Netron](https://github.com/lutzroeder/netron). A properly exported weights file will show a flat
+structure of tensors, while an incorrectly exported file will display nested blocks representing the
+entire model architecture. When viewing the exported model in Netron, you should see something like
+this:
 
 ![image alt>](./conv2d.svg)