pytorch load model from checkpoint

In PyTorch, training deep learning models often involves saving checkpoints to resume training or to use the trained model for inference later. In this tutorial, we will explore how to load a model from a checkpoint in PyTorch using a code example.
Before you begin, make sure you have PyTorch installed. You can install it using:
This code snippet illustrates a basic model training loop and saving the model checkpoint after each epoch.
Now, let's see how to load the saved model checkpoint using PyTorch. We'll assume you want to resume training or use the model for inference:
This code snippet demonstrates how to load the model from a saved checkpoint. Note that you may need to adjust the checkpoint path based on the actual file you want to load.
By following these steps, you can easily save and load PyTorch model checkpoints, allowing you to resume training or use the trained model for various purposes.
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