This article covers the fifth and sixth steps -- evaluating, saving, and using a trained regression model. A good way to see where this series of articles is headed is to take a look at the screenshot ...

A good way to see where this series of articles is headed is to take a look at the screenshot of the demo program in Figure 1. ... However, you cannot load a saved ONNX model using PyTorch. Instead, ...

If you have a prebuilt model, you can run it from a cloud platform such as Azure ML, using a REST API to work with its predictions, or you can export it in the widely supported ONNX (Open Neural ...

According to Facebook, PyTorch 1.0 takes the modular, production-oriented capabilities from Caffe2 and ONNX and combines them with PyTorch's existing flexible, research-focused design to provide a ...

Using the ONNX standard means the optimized models can run with PyTorch, TensorFlow, and other popular machine learning models. The work is the result of a collaboration between Azure AI and ...