candle
rust-gpu
candle | rust-gpu | |
---|---|---|
17 | 82 | |
13,475 | 6,952 | |
4.4% | 0.8% | |
9.9 | 7.7 | |
3 days ago | 14 days 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.
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.
candle
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karpathy/llm.c
Candle already exists[1], and it runs pretty well. Can use both CUDA and Metal backends (or just plain-old CPU).
[1] https://github.com/huggingface/candle
- Best alternative for python
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Is there any LLM that can be installed with out python
Check out Candle! It's a Deep Learning framework for Rust. You can run LLMs in binaries.
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Announcing Kalosm - an local first AI meta-framework for Rust
Kalosm is a meta-framework for AI written in Rust using candle. Kalosm supports local quantized large language models like Llama, Mistral, Phi-1.5, and Zephyr. It also supports other quantized models like Wuerstchen, Segment Anything, and Whisper. In addition to local models, Kalosm supports remote models like GPT-4 and ada embeddings.
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RFC: candle-lora
I have been working on a machine learning library called candle-lora for Candle. It implementes a technique called LoRA (low rank adaptation), which allows you to reduce a model's trainable parameter count by wrapping and freezing old layers.
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ExecuTorch: Enabling On-Device interference for embedded devices
[2] https://github.com/huggingface/candle/issues/313
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[P] Open-source project to run locally LLMs in browser, such as Phi-1.5 for fully private inference
We provide full local inference in browser, by using libraries from Hugging Face like transformers.js or candle for WASM inference.
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Update on the Candle ML framework.
We've first announced Candle, a minimalist ML framework in Rust 6 weeks ago. Since then we've focused on adding various recent models and improved the framework so as to support the necessary features in an efficient way. You can checkout a gallery of the examples, supported models include:
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Should I Haskell or OCaml?
How did you select those two as your options?
I'm just a hobbyist that enjoys programming, and I eventually wanted to expand beyond python. I looked at Haskell and read Learn You a Haskell and did some Exercism exercises but never got anywhere close to being able to use it for real projects. Have been trying to learn about Lisp lately and feel like I've come to a similar dead end.
On the other hand, both Go and Rust have felt fulfilling and practical, with static typing and solid tooling, cross compilations, static binaries, and dependency management that is just a huge breath of fresh air coming from python.
The ML / data science scene is nowhere near as developed as in Python, and I still lean on jupyter/polars/PyTorch here, but I think the candle project[0] seems very interesting. Compiling whisper down to a single CUDA-leveraging binary for fast local transcription is pretty cool!
[0]: https://github.com/huggingface/candle
- Minimalist ML framework for Rust
rust-gpu
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Vcc – The Vulkan Clang Compiler
Sounds cool, but this requires yet another language to learn[0]. As someone who only has limited knowledge in this space, could someone tell me how comparable is the compute functionality of rust-gpu[1], where I can just write rust?
[0] https://github.com/Hugobros3/shady#language-syntax
[1] https://github.com/EmbarkStudios/rust-gpu
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Candle: Torch Replacement in Rust
I don't do anything related to data science, but I feel like doing it in Rust would be nice.
You get operator overloading, so you can have ergonomic matrix operations that are typed also. Processing data on the CPU is fast, and crates like https://github.com/EmbarkStudios/rust-gpu make it very ergonomic to leverage the GPU.
I like this library for creating typed coordinate spaces for graphics programming (https://github.com/servo/euclid), I imagine something similar could be done to create refined types for matrices so you don't do matrix multiplication matrices of invalid sizes
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What's the coolest Rust project you've seen that made you go, 'Wow, I didn't know Rust could do that!'?
Do you mean rust-gpu?
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How a Nerdsnipe Led to a Fast Implementation of Game of Life
And https://github.com/EmbarkStudios/rust-gpu/tree/main/examples with the wgpu runner (here it runs the compute shader)
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What is Rust's potential in game development?
I don't know how major they are considered, but Embark Studios is doing quite a bit of Rust in the open source space, most notably (IMO) rust-gpu and kajiya
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[rust-gpu] How do I run/build my own shaders locally?
The examples in the rust-gpu repository are a good place to start
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Posh: Type-Safe Graphics Programming in Rust
There's another project that's similar that's being used by an actual game company: https://github.com/EmbarkStudios/rust-gpu
They see specific advantages here that would outweigh that negative. It's not my space (I play games, but know next to nothing about graphics programming), but there's at least one argument in the other direction.
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Introducing posh: Type-Safe Graphics Programming in Rust
Could this approach work for compute shaders (GPGPU) as well? So far, I think https://github.com/EmbarkStudios/rust-gpu is the state of the art in that area, but it adds a specific Rust compiler backend for generating SPIR-V rather than leaving that up to the driver. That seems more complicated than it needs to be... but maybe it has advantages too? Thoughts?
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Looking for high level GPU computing crate
https://github.com/embarkstudios/rust-gpu Allows you to create shaders (kernals) in Rust.
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With what languages are video games like League of Legends (most likely) programmed?
Also Embark Studios (formers DICE people) is doing a lot of work with Rust, all open source like Rust GPU https://github.com/EmbarkStudios/rust-gpu
What are some alternatives?
Universal-G-Code-Sender - A cross-platform G-Code sender for GRBL, Smoothieware, TinyG and G2core.
llama.cpp - LLM inference in C/C++
burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. [Moved to: https://github.com/Tracel-AI/burn]
wgpu - Cross-platform, safe, pure-rust graphics api.
tch-rs - Rust bindings for the C++ api of PyTorch.
Rust-CUDA - Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
bCNC - GRBL CNC command sender, autoleveler and g-code editor
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
gsender - Connect to and control Grbl-based CNCs with ease
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
cncjs - A web-based interface for CNC milling controller running Grbl, Marlin, Smoothieware, or TinyG.
DiligentEngine - A modern cross-platform low-level graphics library and rendering framework