ONNX Runtime Offers Free API to Run ML Models 10x Faster
ONNX Runtime is an open-source inference engine from Microsoft that can run machine learning models across platforms with hardware acceleration. It provides a universal execution engine for the ONNX format, allowing models trained in any framework to be optimized and run faster.
Why it matters
ONNX Runtime's free and cross-platform capabilities make it easier for developers to deploy high-performance ML models in their applications, regardless of the original framework used.
Key Points
- 1ONNX Runtime supports models from any ML framework (TensorFlow, PyTorch, scikit-learn, etc.)
- 2It provides hardware acceleration on CPU, GPU, DirectML, TensorRT, and OpenVINO
- 3Offers language support for Python, C++, C#, Java, JavaScript, React Native, and Objective-C
- 4Can often achieve 2-10x faster inference speeds compared to native framework inference
Details
ONNX Runtime is an open-source inference engine developed by Microsoft that solves the problem of model portability across different ML frameworks and platforms. Unlike frameworks like TensorFlow or PyTorch that lock you into their own ecosystem, ONNX Runtime provides a universal execution engine for the ONNX format. This allows you to run models trained in any framework, including PyTorch, TensorFlow, scikit-learn, and XGBoost, with hardware acceleration on CPU, GPU, DirectML, TensorRT, and OpenVINO. The API is available for free and supports a wide range of programming languages, making it easy to integrate into your applications. By optimizing the inference process, ONNX Runtime can often achieve 2-10x faster performance compared to running the models natively.
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