Скачать или смотреть pytorch save model architecture

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PyTorch provides a straightforward way to save both the architecture (model definition) and parameters of a trained model. This tutorial will guide you through the process of saving and loading a PyTorch model using code examples.
Make sure you have PyTorch installed. If not, you can install it using:
For demonstration purposes, let's create a simple neural network using PyTorch. You can replace this with your own model.
You can train the model if you haven't already. For simplicity, we'll skip this step in this tutorial.
Now, let's save the model architecture and parameters.
To load the model back, you need to recreate the model architecture and load the parameters.
Now, loaded_model_instance is ready to be used for inference.
That's it! You've successfully saved and loaded a PyTorch model along with its architecture and parameters. Feel free to adapt this tutorial to your specific use case and model architecture.
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