ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators — the building blocks of machine learning and deep learning models — and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. The following post is a compilation of code samples showing how to evaluate Onnx Models in 10 different programming languages.
#10 R
#9 C++
#8 Java
#7 .NET Core
Tutorial: Detect objects using an ONNX deep learning model - ML.NET
#6 Ruby
#5 Rust
#4 JavaScript
#3 Python
#2 Swift
Convert fast.ai trained image classification model to iOS app via ONNX and Apple Core ML
#1 C
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About the Author
Aaron (Ari) Bornstein is an AI researcher with a passion for history, engaging with new technologies and computational medicine. As an Open Source Engineer at Microsoft’s Cloud Developer Advocacy team, he collaborates with Israeli Hi-Tech Community, to solve real world problems with game changing technologies that are then documented, open sourced, and shared with the rest of the world.
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