To debug the issue compare the outputs of a static tensor (either define one via e.g. torch.ones or save a specific input batch) before saving the model and after loading it in the other notebook. If the results are equal, this would point to a difference in the data processing. On the other hand, if the results are different, either the model creates “random” outputs e.g. via some random operations (call model.eval() to disable dropout layers and check for other random operations) or the saving/loading failed.