Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).
Install-Package Onnx.Net -Version 0.3.1
dotnet add package Onnx.Net --version 0.3.1
<PackageReference Include="Onnx.Net" Version="0.3.1" />
paket add Onnx.Net --version 0.3.1
#r "nuget: Onnx.Net, 0.3.1"
// Install Onnx.Net as a Cake Addin #addin nuget:?package=Onnx.Net&version=0.3.1 // Install Onnx.Net as a Cake Tool #tool nuget:?package=Onnx.Net&version=0.3.1
NuGet packages (1)
Showing the top 1 NuGet packages that depend on Onnx.Net:
C# Binding for the Apache MxNet library. NDArray, Symbolic and Gluon Supported MxNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. MXNet is more than a deep learning project. It is a collection of blue prints and guidelines for building deep learning systems, and interesting insights of DL systems for hackers.
GitHub repositories (1)
Showing the top 1 popular GitHub repositories that depend on Onnx.Net:
.NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. https://mxnet.tech-quantum.com/