ONNX

ONNX (Open Neural Network Exchange) is an open-source, framework-agnostic format designed to enable seamless interoperability between machine learning and deep learning frameworks. It allows models trained in popular frameworks such as PyTorch, TensorFlow, and scikit-learn to be exported into a standardized format for efficient inference and deployment across diverse platforms and environments.

Features of ONNX:

• Framework-independent model representation for improved portability.
• Seamless model exchange between training and inference environments.
• Broad ecosystem support from major AI and ML frameworks.
• Optimized computation graphs for high-performance inference.
• Cross-platform compatibility (Linux, Windows, macOS).
• Strong tooling support for model validation and optimization.
• Designed for both research and production-grade deployments.
• Backed by an active open-source community and industry contributors.

ONNXruntime Usage:

$ sudo su
$ cd /opt
$ source /opt/onnxruntime-venv/bin/activate
$ Check version: python -c "import onnxruntime; print('ONNX Runtime version:', onnxruntime.__version__)"
  

Disclaimer: ONNX and ONNX Runtime are open-source projects developed under the Apache License 2.0 and maintained by a global community of contributors. They are not tied to any specific commercial product unless explicitly stated. The software is provided "as is," without warranties or conditions of any kind. Users are responsible for ensuring proper usage, security, and compliance with applicable licenses and regulations.