transfer-sh-helper-rusted
tract
| transfer-sh-helper-rusted | tract | |
|---|---|---|
| 3 | 20 | |
| 11 | 2,060 | |
| - | 1.6% | |
| 6.5 | 9.8 | |
| 4 months ago | 4 days ago | |
| Rust | Rust | |
| MIT License | Apache 2.0/MIT |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
transfer-sh-helper-rusted
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[Discussion] What crates would you like to see?
I needed a create for my Transfer-sh-cli-app that would compress folders or files to .tar.gz. I searched a bit for some crate that would fit my needs but I didn't really find one. So I created the crate Comprexor, with a very easy interface to compress and decompress files.
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Official /r/rust "Who's Hiring" thread for job-seekers and job-offerers [Rust 1.67]
TransferHelper: Store your transfer.sh links, so you can remember them later and know when they will expire, but now written in Rust.
- A simple cli based Transfer.sh helper
tract
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Are there any ML crates that would compile to WASM?
Tract is the most well known ML crate in Rust, which I believe can compile to WASM - https://github.com/sonos/tract/. Burn may also be useful - https://github.com/burn-rs/burn.
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[Discussion] What crates would you like to see?
tract!!
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tract VS burn - a user suggested alternative
2 projects | 25 Mar 2023
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Machine Learning Inference Server in Rust?
we use tract for inference, integrated into our runtime and services.
- onnxruntime
- Rust Native ML Frameworks?
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Neural networks - what crates to use?
Not for training, but for inference this looks nice: https://github.com/sonos/tract
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Brain.js: GPU Accelerated Neural Networks in JavaScript
There's also tract, from sonos[0]. 100% rust.
I'm currently trying to use it to do speech recognition with a variant of the Conformer architecture (exported to ONNX).
The final goal is to do it in WASM client-side.
[0] https://github.com/sonos/tract
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Serving ML at the Speed of Rust
As the article notes, there isn't any official Rust-native support for any common frameworks.
tract (https://github.com/sonos/tract) seems like the most mature for ONNX (for which TF/PT export is good nowadays), and recently it successfully implemented BERT.
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Run deep neural network models from scratch
There are some DL libraries written in Rust: https://github.com/sonos/tract , https://docs.rs/neuronika/latest/neuronika/index.html . The second one could be used for training, I think.
What are some alternatives?
tracing-oslog - A tracing layer for macOS/iOS's `oslog`
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
boa - Boa is an embeddable and experimental Javascript engine written in Rust. Currently, it has support for some of the language.
MTuner - MTuner is a C/C++ memory profiler and memory leak finder for Windows, PlayStation 4 and 3, Android and other platforms
faer-rs - Linear algebra foundation for the Rust programming language
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
job-descriptions
ncurses-rs - A low-level ncurses wrapper for Rust
xenon-ios - The public source and documentation for Xenon iOS tweak.
linfa - A Rust machine learning framework.
xpc-serde - A Serde serializer for XPC!
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.