BerriAI / litellm
github.com·3d ago
Developer Tools
GitHub Trending·Aug 21·5 min read
microsoft / onnxruntime
TL;DR
ONNX Runtime is a versatile machine-learning accelerator that enhances inference and training across various frameworks like PyTorch and TensorFlow. It optimizes performance on diverse hardware, enabling faster model execution and reduced costs.
✦ Why It Matters
Integrate ONNX Runtime into your existing machine learning projects to improve performance and reduce costs immediately.
Key Takeaways
- Integrate ONNX Runtime for faster model inference.
- Use ONNX Runtime to reduce training time on NVIDIA GPUs.
- Explore extensive documentation and tutorials for implementation.
- Contribute to the project by following the contribution guidelines.
Full Summary
ONNX Runtime serves as a cross-platform accelerator for machine learning, supporting both inference and training. It integrates seamlessly with popular deep learning frameworks such as PyTorch and TensorFlow, as well as classical libraries like scikit-learn and XGBoost.
By utilizing hardware accelerators and applying graph optimizations, ONNX Runtime delivers optimal performance across different operating systems and hardware configurations. For training, it can significantly reduce model training time on multi-node NVIDIA GPUs with minimal code changes.
This capability is particularly beneficial for transformer models, which are widely used in natural language processing tasks. The project encourages community contributions and provides extensive documentation and tutorials to facilitate user engagement.