onnxruntime-rs
csl-mobile-bridge
| onnxruntime-rs | csl-mobile-bridge | |
|---|---|---|
| 2 | 3 | |
| 260 | 23 | |
| - | - | |
| 0.0 | 7.0 | |
| about 2 months ago | 5 days ago | |
| Rust | Rust | |
| Apache License 2.0 | MIT License |
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onnxruntime-rs
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Deep Learning in Rust on GPU with onnxruntime-rs
I did: https://github.com/nbigaouette/onnxruntime-rs/pull/87 but the maintainer seems to be off. I sent an email.
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Interesting results comparing TF and Rust
I have used the https://github.com/nbigaouette/onnxruntime-rs ONNX C++ wrapper on a Pytorch model, and did not see any difference in compute time between ONNX Python and ONNX Rust for GPU.
csl-mobile-bridge
- Looking for a rust developer to write some native bindings
- Looking for a rust developer to write some mobile bindings - Job
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Where can I run a dapp that actually uses the Cardano testnet?
Yeah I get what you mean. Digging deeper, I thought I'd take a look at Yoroi as that's a light wallet. It's made with React Native, so at least that's a plus as far as turning it into a website. However, if you look at how they do it, they use this library that they've made, and it's definitely server-side, but I suppose if you have an RN app then that's not an issue.
What are some alternatives?
tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
cardano-wallet-js - cardano-wallet javascript/typescript client
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
cardano-serialization-lib - This is a library, written in Rust, for serialization & deserialization of data structures used in Cardano's Haskell implementation of Alonzo along with useful utility functions.
deno - A modern runtime for JavaScript and TypeScript.
yoroi - Yoroi
ort - A Rust wrapper for ONNX Runtime
browserify - browser-side require() the node.js way
tractjs - Run ONNX and TensorFlow inference in the browser.
blindai - Confidential AI deployment with secure enclaves :lock:
steelix - Your one stop CLI for ONNX model analysis.
rust - Empowering everyone to build reliable and efficient software.