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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
ezkl is an engine for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). Use it from Python, Javascript, or the command line.
| Date | Stars |
|---|---|
| 2026-07-31 | 1219 |
| 2026-08-04 | 1219 |
| 2026-08-06 | 1219 |
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<h1 align="center"> <br> :thought_balloon: <br> <br> EZKL <br> <br> <br> </h1> > Easy Zero-Knowledge Inference [](https://github.com/zkonduit/ezkl/actions?query=workflow%3ARust) `ezkl` is a library and command-line tool for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). It enables the following workflow: 1. Define a computational graph, for instance a neural network (but really any arbitrary set of operations), as you would normally in pytorch or tensorflow. 2. Export the final graph of operations as an [.onnx](https://onnx.ai/) file and some sample inputs to a `.json` file. 3. Point `ezkl` to the `.onnx` and `.json` files to generate a ZK-SNARK circuit with which you can prove statements such as: > "I ran this publicly available neural network on some private data and it produced this output" [](https://colab.research.google.com/github/zkonduit/ezkl/blob/main/examples/notebooks/simple_demo_public_network_output.ipynb) > "I ran my private neural network on some public data and it produced this output" [](https://colab.research.google.com/github/zkonduit/ezkl/blob/main/examples/notebooks/simple_demo_public_input_output.ipynb) > "I correctly ran this publicly available neural network on some public data and it produced this output" [](https://colab.research.google.com/github/zkonduit/ezkl/blob/main/examples/notebooks/simple_demo_all_public.ipynb) In the backend we use the collaboratively-developed [Halo2](https://github.com/privacy-scaling-explorations/halo2) as a proof system. The generated proofs can then be verified with much less computational resources, including on-chain (with the Ethereum Virtual Machine), in a browser, or on a device. - If you have any questions, we'd love for you to open up a discussion topic in [Discussions](https://github.com/zkonduit/ezkl/discussions). Alternatively, you can join the ✨[EZKL Community Telegram Group](https://t.me/+QRzaRvTPIthlYWMx)💫. - For more technical writeups and details check out our [blog](https://blog.ezkl.xyz/). - To see what you can build with ezkl, check out [cryptoidol.tech](https://cryptoidol.tech/) where ezkl is used to create an AI that judges your singing ... forever. ---------------------- ### Getting Started ⚙️ The easiest way to get started is to try out a notebook. #### Python Install the python bindings by calling. ```bash pip install ezkl ``` Or for the GPU: ```bash pip install ezkl-gpu ``` Google Colab Example to learn how you can train a neural net and deploy an inference verifier onchain for use in other smart contracts. [](https://colab.research.google.com/github/zkonduit/ezkl/blob/main/examples/notebooks/ezkl_demo.ipynb) More notebook tutorials can be found within `examples/notebooks`. #### CLI Install the CLI ``` shell curl https://raw.githubusercontent.com/zkonduit/ezkl/main/install_ezkl_cli.sh | bash ``` https://user-images.githubusercontent.com/45801863/236771676-5bbbbfd1-ba6f-418a-902e-20738ce0e9f0.mp4 For more details visit the [docs](https://docs.ezkl.xyz). The CLI is faster than Python, as it has less overhead. For even more speed and convenience, check out the [remote proving service](https://ei40vx5x6j0.typeform.com/to/sFv1oxvb), which feels like the CLI but is backed by a tuned cluster. Build the auto-generated rust documentation and open the docs in your browser locally. `cargo doc --open` ### Building the Project 🔨 #### Rust CLI You can install the library from source ```bash cargo install --locked --path . ``` `ezkl` now auto-manages solc installation for you. #### Building Python Bindings Python bindings exists
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François Garillot · 4DE3 AD16 FA0A 584B 3C8D C054 3ACB 4CB1 5EA2 FFD6
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:0900af033b5d0d19, llm:Repository topics: ai, cryptography, zero-knowledge, zkml. Description: 'ezkl is an engine for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). Use it from Python, Javascript, or the command line.'
matched fp:0900af033b5d0d19, llm:Repository topics: ai, cryptography, zero-knowledge, zkml. Description: 'ezkl is an engine for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). Use it from Python, Javascript, or the command line.'