https://github.com/gizatechxyz/orion
ONNX Runtime in Cairo 1.0 for verifiable ML inference using STARK
https://github.com/gizatechxyz/orion
cairo-lang deep-learning machine-learning onnx starknet tensorflow
Last synced: 7 months ago
JSON representation
ONNX Runtime in Cairo 1.0 for verifiable ML inference using STARK
- Host: GitHub
- URL: https://github.com/gizatechxyz/orion
- Owner: gizatechxyz
- License: mit
- Created: 2022-04-21T09:40:36.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-08-28T06:11:25.000Z (about 1 year ago)
- Last Synced: 2024-08-28T07:29:18.939Z (about 1 year ago)
- Topics: cairo-lang, deep-learning, machine-learning, onnx, starknet, tensorflow
- Language: Cairo
- Homepage: https://orion.gizatech.xyz
- Size: 47.9 MB
- Stars: 161
- Watchers: 8
- Forks: 81
- Open Issues: 81
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-cairo - `orion` - library for verifiable ML inference in Cairo 1.0 (Libraries)
- awesome-rust-list - Orion - source Framework for Validity and ZK ML โจ. ONNX Runtime in Cairo 1.0 for verifiable ML inference using STARK. [orion.gizatech.xyz](https://orion.gizatech.xyz/) (Machine Learning)
- awesome-rust-list - Orion - source Framework for Validity and ZK ML โจ. ONNX Runtime in Cairo 1.0 for verifiable ML inference using STARK. [orion.gizatech.xyz](https://orion.gizatech.xyz/) (Machine Learning)
README
[](https://github.com/gizatechxyz/orion/actions/workflows/test.yaml)
[](LICENSE)
[](https://github.com/gizatechxyz/orion/issues?q=is%3Aissue+is%3Aopen)
[](https://discord.gg/kvqVYbCpU3)
# Orion: An Open-source Framework for Validity and ZK ML โจ
[](#contributors-)
๐จโ ๏ธ๐จโ ๏ธ๐จโ ๏ธ
**This project has been archived and is no longer maintained. We're now developing [LuminAIR](https://github.com/gizatechxyz/LuminAIR), a new and super-efficient zkML framework based on a custom AIR, proven with the [STWO](https://github.com/starkware-libs/stwo) Prover.**
**We'd like to thank all the Orion contributors and hope to see you again in this new journey.**
๐จโ ๏ธ๐จโ ๏ธ๐จโ ๏ธ
---
Orion is an open-source, community-driven framework dedicated to Provable Machine Learning. It provides essential components and a new ONNX runtime for building verifiable Machine Learning models using [STARKs](https://starkware.co/stark/).
## ๐ค What is ONNX Runtime?
ONNX (Open Neural Network Exchange), is an open-source standard created to represent deep learning models. The aim of its development was to enable interoperability among diverse deep learning frameworks, like TensorFlow or PyTorch. By offering a universal file format, ONNX allows models trained in one framework to be readily applied in another for inference, eliminating the need for model conversion.
Ensuring compatibility with ONNX operators facilitates integration into the ONNX ecosystem. This enables researchers and developers to pre-train models using their preferred framework, before executing verifiable inferences with Orion.
## ๐ฑ Where to start?
You can check our official docs [here](https://orion.gizatech.xyz/welcome/readme).
- ๐งฑ [Framework](https://orion.gizatech.xyz/v/develop/framework/get-started): The building blocks for Verifiable Machine Learning models.
- ๐ [Hub](https://orion.gizatech.xyz/v/develop/hub/algorithms): A curated collection of ML models and spaces built by the community using Orion framework.
- ๐ [Academy](https://orion.gizatech.xyz/v/develop/academy/tutorials): Resources and tutorials for learning how to build ValidityML models using Orion.
## ๐ Join the community!
Join the community and help build a safer and transparent AI in our [Discord](https://discord.gg/kvqVYbCpU3)!
## ๐ Orion Usage
- For an insightful overview of impressive proof of concepts, models, and tutorials created by our community, please visit [Orion Usage](https://github.com/gizatechxyz/orion/blob/main/orion-usage.md).
- Discover a curated list of tutorials and models developed using Orion in [Orion-Hub](https://github.com/gizatechxyz/Orion-Hub).
## โ๏ธ Authors & contributors
For a full list of all authors and contributors, see [the contributors page](https://github.com/franalgaba/onnx-cairo/graphs/contributors).
## License
This project is licensed under the **MIT license**.
See [LICENSE](https://github.com/franalgaba/onnx-cairo/blob/main/LICENSE) for more information.
## Contributors โจ
Thanks goes to these wonderful people:

Fran Algaba
๐ป

raphaelDkhn
๐ป

Lanre Ojetokun
๐ป ๐

Moody Salem
๐ป ๐

Roy Rotstein
๐ป

omahs
๐

Kazeem Hakeem
๐ป

dblanco
๐ป

BemTG
๐ป ๐

danilowhk
๐ป

Falco R
๐ป

dincerguner
๐ป

Rich Warner
๐ป

Daniel Bejarano
๐

vikkydataseo
๐

Daniel
๐ป

Charlotte
๐ป

0xfulanito
๐ป

0x73e
๐ป

Thomas S. Bauer
๐ป

Andres
๐ป

Ephraim Chukwu
๐ป

Bal7hazar
๐

Tony Stark
๐

Mahmoud Mohajer
๐ป

HappyTomatoo
๐

Bilgin Koรงak
๐ป

akhercha
๐ป

Vid Kersic
๐ป

Trunks @ Carbonable
๐

canacechan
๐ป

Tristan
๐ป

Kugo
๐

Beeyoung
๐ป
This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!