repugnant-pickle
burn
repugnant-pickle | burn | |
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1 | 34 | |
20 | 4,845 | |
- | - | |
4.7 | 8.9 | |
4 months ago | 5 months ago | |
Rust | Rust | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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repugnant-pickle
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Introducing repugnant-pickle, a crate for scraping Python Pickle files in a basic way. Notable, it can deal with (some) PyTorch model files.
The repo has a detailed README: https://github.com/KerfuffleV2/repugnant-pickle
burn
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Burn 0.10.0 Released 🔥 (Deep Learning Framework)
Release Note: https://github.com/burn-rs/burn/releases/tag/v0.10.0
- Deep Learning Framework in Rust: Burn 0.10.0 Released
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Why Rust Is the Optimal Choice for Deep Learning, and How to Start Your Journey with the Burn Deep Learning Framework
The comprehensive, open-source deep learning framework in Rust, Burn, has recently undergone significant advancements in its latest release, highlighted by the addition of The Burn Book 🔥. There has never been a better moment to embark on your deep learning journey with Rust, as this book will guide you through your initial project, providing extensive explanations and links to relevant resources.
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Candle: Torch Replacement in Rust
Burn (deep learning framework in rust) has WGPU backend (WebGPU) already. Check it out https://github.com/burn-rs/burn. It was released recently.
- Burn – A Flexible and Comprehensive Deep Learning Framework in Rust
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Announcing Burn-Wgpu: New Deep Learning Cross-Platform GPU Backend
For more details about the latest release see the release notes: https://github.com/burn-rs/burn/releases/tag/v0.8.0.
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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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Any working wgpu compute example that would run in a browser?
We, the burn team, are working on the wgpu backend (WebGPU) for Burn deep learning framework. You can check out the current state: https://github.com/burn-rs/burn/tree/main/burn-wgpu
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I’ve fallen in love with rust so now what?
Here is the project: https://github.com/burn-rs/burn
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Is anyone doing Machine Learning in Rust?
Disclaimer, I'm the main author of Burn https://burn-rs.github.io.
What are some alternatives?
lucia - A flexible client API framework as well as a set of API collections
candle - Minimalist ML framework for Rust
smolrsrwkv - A relatively basic implementation of RWKV in Rust written by someone with very little math and ML knowledge. Supports 32, 8 and 4 bit evaluation. It can also directly load PyTorch RWKV models.
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
gda_compute - A GPU/CPU compute library written in rust focusing on computation on ndim Arrays
tch-rs - Rust bindings for the C++ api of PyTorch.
Synthic - Automatically generate gameboy music using machine learning
Graphite - 2D raster & vector editor that melds traditional layers & tools with a modern node-based, non-destructive, procedural workflow.
deku - Declarative binary reading and writing: bit-level, symmetric, serialization/deserialization
tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference [Moved to: https://github.com/sonos/tract]
L2 - l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust
wgpu - Cross-platform, safe, pure-rust graphics api.