16 releases
Uses new Rust 2024
| 2.0.0-rc.11 | Jan 7, 2026 |
|---|---|
| 2.0.0-rc.10 | Jun 1, 2025 |
| 2.0.0-rc.9 | Nov 21, 2024 |
| 2.0.0-rc.4 | Jul 7, 2024 |
| 2.0.0-alpha.2 | Nov 28, 2023 |
#581 in Machine learning
475,840 downloads per month
Used in 273 crates
(14 directly)
220KB
4.5K
SLoC
ort is a Rust interface for performing hardware-accelerated inference & training on machine learning models in the Open Neural Network Exchange (ONNX) format.
Based on the now-inactive onnxruntime-rs crate, ort is primarily a wrapper for Microsoft's ONNX Runtime library, but offers support for other pure-Rust runtimes.
ort with ONNX Runtime is super quick - and it supports almost any hardware accelerator you can think of. Even still, it's light enough to run on your users' devices.
When you need to deploy a PyTorch/TensorFlow/Keras/scikit-learn/PaddlePaddle model either on-device or in the datacenter, ort has you covered.
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π FOSS projects using ort
Open a PR to add your project here π
- Koharu uses
ortto detect, OCR, and inpaint manga pages. - BoquilaHUB uses
ortfor local AI deployment in biodiversity conservation efforts. - Magika uses
ortfor content type detection. - Text Embeddings Inference (TEI) uses
ortto deliver high-performance ONNX runtime inference for text embedding models. sbv2-apiis a fast implementation of Style-BERT-VITS2 text-to-speech usingort.- CamTrap Detector uses
ortto detect animals, humans and vehicles in trail camera imagery. - oar-ocr A comprehensive OCR library, built in Rust with
ortfor efficient inference. - retto uses
ortfor reliable, fast ONNX inference of PaddleOCR models on Desktop and WASM platforms. - Ahnlich uses
ortto power their AI proxy for semantic search applications. - Valentinus uses
ortto provide embedding model inference inside LMDB. - edge-transformers uses
ortfor accelerated transformer model inference at the edge. FastEmbed-rsusesortfor generating vector embeddings, reranking locally.- Ortex uses
ortfor safe ONNX Runtime bindings in Elixir. - SilentKeys uses
ortfor fast, on-device real-time dictation with NVIDIA Parakeet and Silero VAD.
Dependencies
~0β2MB
~27K SLoC