SciSharp.TensorFlow.Redist-Windows-GPU 2.10.1

There is a newer version of this package available.
See the version list below for details.
dotnet add package SciSharp.TensorFlow.Redist-Windows-GPU --version 2.10.1                
NuGet\Install-Package SciSharp.TensorFlow.Redist-Windows-GPU -Version 2.10.1                
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="SciSharp.TensorFlow.Redist-Windows-GPU" Version="2.10.1" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add SciSharp.TensorFlow.Redist-Windows-GPU --version 2.10.1                
#r "nuget: SciSharp.TensorFlow.Redist-Windows-GPU, 2.10.1"                
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install SciSharp.TensorFlow.Redist-Windows-GPU as a Cake Addin
#addin nuget:?package=SciSharp.TensorFlow.Redist-Windows-GPU&version=2.10.1

// Install SciSharp.TensorFlow.Redist-Windows-GPU as a Cake Tool
#tool nuget:?package=SciSharp.TensorFlow.Redist-Windows-GPU&version=2.10.1                

SciSharp.TensorFlow.Redist-Windows-GPU contains the Google TensorFlow C library GPU version 2.10.1 redistributed as a NuGet package.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
  • .NETStandard 2.0

    • No dependencies.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on SciSharp.TensorFlow.Redist-Windows-GPU:

Package Downloads
NsfwSpy

NsfwSpy is an image and video classifier used to identify explicit/pornographic content using machine learning.

ImageClassificationGPU

A ML.NET wrapper to ease image classification.

NboxTrainer

Nbox Trainer is library-wrapper for easy creating trainer ml models of image classification with GPU acceleration. Used ML.Net and Tensorflow

GitHub repositories (3)

Showing the top 3 popular GitHub repositories that depend on SciSharp.TensorFlow.Redist-Windows-GPU:

Repository Stars
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
NsfwSpy/NsfwSpy.NET
A .NET image and video classifier used to identify explicit/pornographic content written in C#.
SciSharp/SciSharp-Stack-Examples
Practical examples written in SciSharp's machine learning libraries
Version Downloads Last updated
2.10.3 62,678 6/21/2023
2.10.2 8,897 5/14/2023
2.10.1 6,828 4/27/2023
2.10.0 27,691 11/11/2022
2.7.0 38,125 12/11/2021
2.6.0 23,390 8/13/2021
2.5.0 10,461 5/23/2021
2.4.0 39,410 12/15/2020
2.3.1 133,136 10/8/2020
2.3.0 11,256 8/31/2020
1.15.1 12,065 2/28/2020
1.14.1 6,174 11/23/2019
1.14.0 71,301 7/30/2019