ONNX Runtime is an open-source project that enables optimized execution of machine learning models across diverse platforms and frameworks. It provides a unified API for deploying models in production environments with high performance and low latency.

Key Features

  • 🚀 High-performance inference with support for CPU, GPU, and other accelerators
  • 📦 Cross-platform compatibility (Windows, Linux, macOS) and multiple languages (Python, C++, etc.)
  • 🧠 Model optimization through graph execution and quantization
  • 🌐 Integration with popular frameworks like TensorFlow, PyTorch, and Scikit-learn

Use Cases

  • 📊 Deploying models in edge devices (e.g., IoT, mobile)
  • 🖥️ Accelerating AI applications in cloud environments
  • 🔄 Reusing models trained in different frameworks

Getting Started

For hands-on experience, check out our Quick Start Guide to deploy your first model.

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Explore more about ONNX Runtime capabilities or model optimization techniques.

model_optimization_flow

This tool is ideal for developers aiming to maximize efficiency while minimizing resource consumption.

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