candle

You are correct. This project is "on the CPU", so it will not utilize your GPU for computation. If you would like to try out a Rust framework that does support GPUs, Candle https://github.com/huggingface/candle/tree/main may be worth exploring

We used candle[0], which uses cudarc and the metal crate under the hood. That means we run on nvidia hardware in production and can test locally on macbooks with smaller models. I would certainly like to use non nvidia hardware but at this point it's not a priority. The subset of tensor operations needed to run the forward pass of LLMs isn't as large as you'd think though. [0] https://github.com/huggingface/candle

Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use https://github.com/huggingface/candle

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

I switched from python to rust for my AI stuff. Honestly, I don't care about the things people say rust is used for. I like it because the package manager, testing, and typings being built into the ecosystem by default makes it so easy to build. VS Python where it all can be done, but you need to then maintain all of those separate tools. The overhead of writing Rust is less than the overhead of dealing with the Python ecosystem. And then you have all the benefits of Rust everyone mentions more often... one other thing no one mentions is the feedback loop between a strongly typed language and copilots ability to more accurately generate code. That being said, there is a real shortage of Rust software for Rust only projects. I ended up writing a wrapper for Llama.cpp and open ai API [0] because I needed it and couldn't find anything out th

I deployed a ML solution in Rust back in 2020 (tch-rs instead of tensorflow, though), so this has been possible for a while. Surprisingly I saw some impressive speed gains vs python (and vs JS, tried that one as well), probably because I was running tons on images through it and the percentage of time spent doing inference wasn't very high. Deployment wasn't the easiest, but doable. Instead of jumping on the tensorflow or torch boat, when doing Rust today I would consider using https://github.com/huggingface/candle