https://github.com/onnx/onnx-r

R Interface to Open Neural Network Exchange (ONNX)
https://github.com/onnx/onnx-r

cran deep-learning deep-neural-networks onnx rstats

Last synced: 3 months ago
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R Interface to Open Neural Network Exchange (ONNX)

• Host: GitHub
• URL: https://github.com/onnx/onnx-r
• Owner: onnx
• License: other
• Created: 2018-03-10T05:08:36.000Z (almost 7 years ago)
• Default Branch: main
• Last Pushed: 2023-07-07T16:55:05.000Z (over 1 year ago)
• Last Synced: 2024-10-30T02:03:52.453Z (3 months ago)
• Topics: cran, deep-learning, deep-neural-networks, onnx, rstats
• Language: R
• Homepage: https://onnx.ai/onnx-r/
• Size: 842 KB
• Stars: 44
• Watchers: 16
• Forks: 13
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE

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**Note**: This package has been maintained by [@terrytangyuan](https://github.com/terrytangyuan) since 2018. Please [consider sponsoring](https://github.com/sponsors/terrytangyuan)!



This is the R Interface to [Open Neural Network Exchange (ONNX)](https://onnx.ai/). 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).

ONNX is [widely supported](https://onnx.ai/supported-tools) and can be found in many frameworks, tools, and hardware. Enabling interoperability between different frameworks and streamlining the path from research to production helps increase the speed of innovation in the AI community. 

Please visit [here](https://onnx.ai/onnx-r/) for tutorials and API reference for using ONNX in R.