Project Introduction: ORT
ort is an unofficial wrapper for the ONNX Runtime 1.19, designed specifically for the Rust programming language. This project is based on the now inactive onnxruntime-rs. ONNX Runtime is a platform that enhances machine learning (ML) inference and training by leveraging the capabilities of both CPUs and GPUs, allowing for faster and more efficient processing.
Documentation
For those interested in using ort, several resources are available:
- Guide: A comprehensive walkthrough can be found in the Guide.
- API Reference: Detailed API documentation is accessible here.
- Examples: Practical examples and applications of
ortcan be explored on GitHub. - Migration Guide: Information on transitioning from version 1.x to version 2.0 is available here.
Support and Community
ort provides several avenues for support and community engagement:
- Discord: Join the discussion on Discord in the #ort-discussions channel here.
- GitHub Discussions: Engage with the community and developers on GitHub Discussions.
- Email: Direct communication is available via email at [email protected].
Projects Leveraging ort
Several high-profile projects incorporate ort to enhance their functionality:
- Twitter: Uses
ortto deliver personalized homepage recommendations to its vast user base. - Bloop: Employs
ortfor its semantic code search capabilities. - edge-transformers: Utilizes
ortfor efficient transformer model inference at the edge. - Ortex: Provides ONNX Runtime bindings in Elixir, thanks to
ort. - Supabase: Uses
ortto eliminate cold start delays for their edge functions. - Lantern: Integrates
ortto enable embedding model inference within Postgres databases. - Magika: Leverages
ortfor content type detection precision. sbv2-api: Implements a fast Style-BERT-VITS2 text-to-speech solution usingort.
Sponsorship
Support for ort can be provided through donations and sponsorships. Information on how to contribute can be found via the Open Collective platform. Sponsorship helps maintain and improve the project, ensuring its continued success and availability for all users.
ort is a powerful tool that continues to be an essential part of many technological advancements, offering speed and efficiency in ML processes across various domains.