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In this tutorial, the focus is on converting models into the ONNX format to utilize ONNX Runtime's capabilities. The discussion highlights compatibility with significant machine learning libraries, specifically PyTorch, TensorFlow, and Scikit-learn. It emphasizes the importance of identifying the training framework used for your model, as different converters are available: Keras to ONNX, TensorFlow to ONNX, Scikit-learn to ONNX, and built-in support for PyTorch via `torch.onnx`. The tutorial uses a simple example from the PyTorch documentation, illustrating how to convert a pre-trained model like AlexNet to the ONNX format.
