
ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
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 →
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 →
Get Started & Resources
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General Information: onnxruntime.ai
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Usage documentation and tutorials: onnxruntime.ai/docs
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YouTube video tutorials: youtube.com/@ONNXRuntime
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Upcoming Release Roadmap
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Companion sample repositories:
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Plugin EP repositories:
- ONNX Runtime QNN Plugin EP: onnxruntime/onnxruntime-qnn
Releases
The current release and past releases can be found here: https://github.com/microsoft/onnxruntime/releases.
For details on the upcoming release, including release dates, announcements, features, and guidance on submitting feature requests, please visit the release roadmap: https://onnxruntime.ai/roadmap.