52 lines
6.5 KiB
Markdown
52 lines
6.5 KiB
Markdown
<p align="center"><img width="50%" src="docs/images/ONNX_Runtime_logo_dark.png" /></p>
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**ONNX Runtime is a cross-platform inference and training machine-learning accelerator**.
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**ONNX Runtime inference** can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. [Learn more →](https://www.onnxruntime.ai/docs/#onnx-runtime-for-inferencing)
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**ONNX Runtime training** can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. [Learn more →](https://www.onnxruntime.ai/docs/#onnx-runtime-for-training)
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## Get Started
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**General Information**: [onnxruntime.ai](https://onnxruntime.ai)
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**Usage documention and tutorials**: [onnxruntime.ai/docs](https://onnxruntime.ai/docs)
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**Companion sample repositories**:
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- ONNX Runtime Inferencing: [microsoft/onnxruntime-inference-examples](https://github.com/microsoft/onnxruntime-inference-examples)
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- ONNX Runtime Training: [microsoft/onnxruntime-training-examples](https://github.com/microsoft/onnxruntime-training-examples)
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## Build Pipeline Status
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|System|CPU|GPU|EPs|
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|---|---|---|---|
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|Windows|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=9)|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=10)|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=47)|
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|Linux|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=11)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=64)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=110)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=78)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=86)|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=12)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=45)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=140)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=84)|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=110)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=55)|
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|Mac|[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=13)<br>[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=65)|||
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|Android|||[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=53)|
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|iOS|||[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=134)|
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|WebAssembly|||[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=161)|
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## Data/Telemetry
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Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the [privacy statement](docs/Privacy.md) for more details.
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## Contributions and Feedback
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We welcome contributions! Please see the [contribution guidelines](CONTRIBUTING.md).
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For feature requests or bug reports, please file a [GitHub Issue](https://github.com/Microsoft/onnxruntime/issues).
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For general discussion or questions, please use [GitHub Discussions](https://github.com/microsoft/onnxruntime/discussions).
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## Code of Conduct
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/)
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or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
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## License
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This project is licensed under the [MIT License](LICENSE).
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