tract
ml5-library
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tract | ml5-library | |
---|---|---|
20 | 16 | |
2,050 | 6,349 | |
2.9% | 0.8% | |
9.8 | 0.0 | |
6 days ago | 4 months ago | |
Rust | JavaScript | |
Apache 2.0/MIT | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
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.
ml5-library
- Why do people curse JS so much, but also say it's better than Python
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Riffr - Create Photo Montages in the Browser with some ML Magic✨
Important APIs - ml5 for in-browser detection, face-api that uses tensorflow-node to accelerate on-server detection. VueUse for a bunch of useful component tools like the QR Code generator. Yahoo's Gifshot for creating gif files in-browser etc.
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Contributing to WebSockets – Cryptocurrency Users
> Have we seen any creator of a deep learning library, take a similar position if not stopping any support for anyone using it for mass surveillance?
ml5.js license:
> This license gives everyone as much permission to work with this software as possible as long as they comply with the ml5.js Code of Conduct [...]
ml5.js code of conduct:
> Do not: [...] Use ml5.js to build tools of mass surveillance and prediction to repress the rights of people
https://github.com/ml5js/ml5-library/blob/main/LICENSE.md
Not sure how enforcable this is but it exists.
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Brain.js: GPU Accelerated Neural Networks in JavaScript
See also: https://ml5js.org/
"The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies."
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10 Mind Blowing JavaScript libraries Of 2022 (I mean it Javascript Noob)
(5) ml5.js
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Top 5 JavaScript Libraries for Machine Learning, Deep Learning
ML.js
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[Showoff Saturday] I made a captcha prototype that requires a banana
I used ml5js.org , p5js.org and https://teachablemachine.withgoogle.com to train the Banana images. When you create a new image project on Teachable Machine, you can output the p5js and basically use it right out of the box - I customized js, css, and html from there.
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My First 30 Days of 100 Days of Code.
Going forward: I'll be 100% into JavaScript. You can use JavaScript in so many fields nowadays. Websites React, Mobile Apps React Native, Machine Learning TensorFlow & ML5, Desktop Applications Electron, and of course the backend Node as well. It's kind of a no-brainer. Of course, they all have specific languages that are better, but for now, JavaScript is a bit of a catch-all.
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PyTorch vs. TensorFlow in 2022
Yeah they made ml5.js for this reason: https://ml5js.org/
I do feel like Google could do better communicating all of their different tools though. Their ecosystem is large and pretty confusing - they've got so many projects going on at once that it always seems like everyone gets fed up with them before they take a second pass and make them more friendly to newcomers.
Facebook seems to have taken a much more focused approach as you can see with PyTorch Live
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[D] Are you using PyTorch or TensorFlow going into 2022?
From other comments, a lot of JavaScript developers who want to use TensorFlow had never heard of TensorFlow.js or ml5.js!
What are some alternatives?
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
tfjs-models - Pretrained models for TensorFlow.js
MTuner - MTuner is a C/C++ memory profiler and memory leak finder for Windows, PlayStation 4 and 3, Android and other platforms
handpose-facemesh-demos - 🎥🤟 8 minimalistic templates for tfjs mediapipe handpose and facemesh
wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
hal9ai - Hal9 — Data apps powered by code and LLMs [Moved to: https://github.com/hal9ai/hal9]
ncurses-rs - A low-level ncurses wrapper for Rust
maze-lightning - This simple project approximates the shape of lightning by generating a random maze using Randomized Prim's algorithm and solving it using breadth-first search.
linfa - A Rust machine learning framework.
bias-monitor - A Chrome Extension that promotes politically diverse news reading with Artificial Intelligence!
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly