mirror of
https://github.com/pykeio/ort
synced 2026-04-25 16:34:55 +02:00
56 lines
4.5 KiB
Markdown
56 lines
4.5 KiB
Markdown
<div align=center>
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<img src="https://parcel.pyke.io/v2/cdn/assetdelivery/ortrsv2/docs/trend-banner.png" width="350px">
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<hr />
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<a href="https://app.codecov.io/gh/pykeio/ort" target="_blank"><img alt="Coverage Results" src="https://img.shields.io/codecov/c/gh/pykeio/ort?style=for-the-badge"></a> <a href="https://crates.io/crates/ort" target="_blank"><img alt="Crates.io" src="https://img.shields.io/crates/d/ort?style=for-the-badge"></a> <a href="https://opencollective.com/pyke-osai" target="_blank"><img alt="Open Collective backers and sponsors" src="https://img.shields.io/opencollective/all/pyke-osai?style=for-the-badge&label=sponsors"></a>
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<br />
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<a href="https://crates.io/crates/ort" target="_blank"><img alt="Crates.io" src="https://img.shields.io/crates/v/ort?style=for-the-badge&label=ort&logo=rust"></a> <img alt="ONNX Runtime" src="https://img.shields.io/badge/onnxruntime-v1.24.4-blue?style=for-the-badge&logo=cplusplus">
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<br />
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</div>
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`ort` is a Rust interface for performing hardware-accelerated inference & training on machine learning models in the [Open Neural Network Exchange](https://onnx.ai/) (ONNX) format.
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Based on the now-inactive [`onnxruntime-rs`](https://github.com/nbigaouette/onnxruntime-rs) crate, `ort` is primarily a wrapper for Microsoft's [ONNX Runtime](https://onnxruntime.ai/) library, but offers support for [other pure-Rust runtimes](https://ort.pyke.io/backends).
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`ort` with ONNX Runtime is super quick - and it supports almost [any hardware accelerator](https://ort.pyke.io/perf/execution-providers) you can think of. Even still, it's light enough to run on your users' devices.
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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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## 📖 Documentation
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- [Guide](https://ort.pyke.io/)
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- [API reference](https://docs.rs/ort/2.0.0-rc.12/ort/)
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- [Examples](https://github.com/pykeio/ort/tree/main/examples)
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- [Migrating from v1.x to v2.0](https://ort.pyke.io/migrating/v2)
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## 🤔 Support
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- [Discord: `#🦀｜ort-general`](https://discord.gg/uQtsNu2xMa)
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- [GitHub Discussions](https://github.com/pykeio/ort/discussions)
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## 🌠 Backers
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<a href="https://opencollective.com/pyke-osai">
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<img src="https://opencollective.com/pyke-osai/backers.svg" />
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</a>
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## 💖 FOSS projects using `ort`
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<sub>[Open a PR](https://github.com/pykeio/ort/pulls) to add your project here 🌟</sub>
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<!--
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This section only showcases projects with OSI-approved licenses: https://opensource.org/licenses
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Businesses that sponsor pyke will appear at the top of the README instead!
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-->
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- **[Text Embeddings Inference (TEI)](https://github.com/huggingface/text-embeddings-inference)** uses `ort` to deliver high-performance ONNX Runtime inference for text embedding models.
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- **[Magika](https://github.com/google/magika)** uses `ort` for neural network-based file type detection.
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- **[retto](https://github.com/NekoImageLand/retto)** uses `ort` for reliable, fast ONNX inference of PaddleOCR models on Desktop and WASM platforms.
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- **[edge-transformers](https://github.com/npc-engine/edge-transformers)** uses `ort` for accelerated transformer model inference at the edge.
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- **[`sbv2-api`](https://github.com/neodyland/sbv2-api)** is a fast implementation of Style-BERT-VITS2 text-to-speech using `ort`.
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- **[BoquilaHUB](https://github.com/boquila/boquilahub/)** uses `ort` for local AI deployment in biodiversity conservation efforts.
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- **[CamTrap Detector](https://github.com/bencevans/camtrap-detector)** uses `ort` to detect animals, humans and vehicles in trail camera imagery.
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- **[Ortex](https://github.com/relaypro-open/ortex)** uses `ort` for safe ONNX Runtime bindings in Elixir.
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- **[oar-ocr](https://github.com/GreatV/oar-ocr)** A comprehensive OCR library, built in Rust with `ort` for efficient inference.
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- **[`FastEmbed-rs`](https://github.com/Anush008/fastembed-rs)** uses `ort` for generating vector embeddings, reranking locally.
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- **[Ahnlich](https://github.com/deven96/ahnlich)** uses `ort` to power their AI proxy for semantic search applications.
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- **[Murmure](https://github.com/Kieirra/murmure)** uses `ort` as its core engine, leveraging NVIDIA Parakeet to deliver fully local, free, private and cross‑platform Speech‑to‑Text enhanced with LLM post‑processing.
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- **[Valentinus](https://github.com/kn0sys/valentinus)** uses `ort` to provide embedding model inference inside LMDB.
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- **[SilentKeys](https://github.com/gptguy/silentkeys)** uses `ort` for fast, on-device real-time dictation with NVIDIA Parakeet and Silero VAD.
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