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Branch to update eol notice #176

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Archiving Notice
sfblackl-intel Jan 25, 2023
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Update README.md
rdower Jan 25, 2023
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Merge branch 'pytorch:main' into main
vthaniel Jul 8, 2023
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Update README.md
vthaniel Jul 8, 2023
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vthaniel Jul 8, 2023
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7 changes: 7 additions & 0 deletions README.md
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Expand Up @@ -211,6 +211,13 @@ Note: ONNX Runtime is not required to run the MoE layer. It is integrated in sta

</div>

**EOL NOTICE : OpenVINO™ integration with Torch-ORT will no longer be supported as of OpenVINO™ 2023.0 release.**

If you are looking to deploy your PyTorch models on Intel based devices, you have a few options.
If you prefer the native PyTorch framework APIs, consider using the Intel Extension for PyTorch (IPEX). Another option is to utilize [OpenVINO Model Conversion API](https://docs.openvino.ai/2023.0/openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html),which enables the automatic importation and conversion of standard PyTorch models during runtime. It is not necessary to convert your PyTorch models offline now.

**END OF EOL NOTICE**

ONNX Runtime for PyTorch supports PyTorch model inference using ONNX Runtime and Intel® OpenVINO™.

It is available via the torch-ort-infer python package. This package enables OpenVINO™ Execution Provider for ONNX Runtime by default for accelerating inference on various Intel® CPUs, Intel® integrated GPUs, and Intel® Movidius™ Vision Processing Units - referred to as VPU.
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