autograd-rs VS rust-bert

Compare autograd-rs vs rust-bert and see what are their differences.

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autograd-rs rust-bert
1 7
0 2,415
- -
6.9 6.8
9 months ago about 2 months ago
Rust Rust
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.

autograd-rs

Posts with mentions or reviews of autograd-rs. We have used some of these posts to build our list of alternatives and similar projects.

rust-bert

Posts with mentions or reviews of rust-bert. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-07.
  • How to leverage the state-of-the-art NLP models in Rust
    3 projects | /r/infinilabs | 7 Jun 2023
    brew install libtorch brew link libtorch brew ls --verbose libtorch | grep dylib export LIBTORCH=$(brew --cellar pytorch)/$(brew info --json pytorch | jq -r '.[0].installed[0].version') export LD_LIBRARY_PATH=${LIBTORCH}/lib:$LD_LIBRARY_PATH git clone https://github.com/guillaume-be/rust-bert.git cd rust-bert ORT_STRATEGY=system cargo run --example sentence_embeddings
  • Transformers.js
    9 projects | news.ycombinator.com | 16 Mar 2023
    I'd like to use this transformer model in rust (because it's on the backend, because I can use data munging and it will be faster, and for other reasons). It looks like a good model! But, it doesn't compile on Apple Silicon for wierd linking issues that aren't apparent - https://github.com/guillaume-be/rust-bert/issues/338. I've spent a large part of today and yesterday attempting to find out why. The only other library that I've found for doing this kind of thing programmatically (particularly sentiment analysis) is this (https://github.com/JohnSnowLabs/spark-nlp). Some of the models look a little older, which is OK, but it does mean that I'd have to do this in another language.

    Does anyone know of any sentiment analysis software that can be tuned (other than VADER - I'm looking for more along the lines of a transformer model) - like BERT, but is pretrained and can be used in Rust or Python? Otherwise I'll probably using spark-nlp and having to spin another process.

    Thanks.

  • Running large language models like ChatGPT on a single GPU
    7 projects | news.ycombinator.com | 20 Feb 2023
    Give this a look: https://github.com/guillaume-be/rust-bert

    If you have Pytorch configured correctly, this should "just work" for a lot of the smaller models. It won't be a 1:1 ChatGPT replacement, but you can build some pretty cool stuff with it.

    > it's basically Python or bust in this space

    More or less, but that doesn't have to be a bad thing. If you're on Apple Silicon, you have plenty of performance headroom to deploy Python code for this. I've gotten this library to work on systems with as little as 2gb of memory, so outside of ultra-low-end use cases, you should be fine.

  • Self-hosted Whisper-based voice recognition server for open Android phones
    2 projects | news.ycombinator.com | 13 Feb 2023
    I suspect something similar is possible with ChatGPT. Using the GPT-neo-125m model I've been able to get some really convincing (if lackluster) answers on 4 core ARM hardware and less than 2gb of memory. With enough sampling, you can get legible paragraph-length responses out in less than 10 seconds; that's pretty good for an offline program in my book.

    I'm using rust-bert to serve it over a Discord bot, similar to one of their examples[0]. It's running on Oracle VCPUs right now, but with dedi hardware and ML acceleration I can imagine the field moving really quickly.

    [0] https://github.com/guillaume-be/rust-bert/blob/master/exampl...

  • Ask HN: What AI developer tools do you wish you'd discovered sooner?
    2 projects | news.ycombinator.com | 12 Feb 2023
    Maybe a little played-out, but I've been having a blast with the rust-bert library this weekend: https://github.com/guillaume-be/rust-bert

    With a little fanagling, you can get the GPT-Neo-1.3b model running on those free Oracle ARM VMs you can provision. I'm impressed, especially with the performance of the smallest model that uses less than a gig of memory.

  • Ask HN: Has anyone made a toy that integrates ChatGPT with voice into a toy?
    2 projects | news.ycombinator.com | 9 Feb 2023
    Nope, but it's probably possible on a smaller, hobbyist scale. I've been playing with a few GPT libraries this week (namely rust-bert[0]) and I've been really impressive with local generation results on my crappy 2 core netbook. I can get 2 sentences to generate in ~5 seconds, which is pretty good in my book.

    Armed with a Pi-style SBC and your AI library of choice, I bet you could get pretty far implementing some stuff. Bonus points if you use Whisper for speech-to-text, and double brownie points if you can get an AI voice to read the generation back.

    [0] https://github.com/guillaume-be/rust-bert/tree/master/exampl...

  • [D] Is Rust stable/mature enough to be used for production ML? Is making Rust-based python wrappers a good choice for performance heavy uses and internal ML dependencies in 2021?
    8 projects | /r/MachineLearning | 30 Dec 2021
    If you are using BERT models and some miscellaneous other related stuff then you should check out the rust-bert and Bert Sentence repos https://github.com/guillaume-be/rust-bert

What are some alternatives?

When comparing autograd-rs and rust-bert you can also consider the following projects:

miniboosts - A collection of boosting algorithms written in Rust 🦀

Dlib - A toolkit for making real world machine learning and data analysis applications in C++

corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.

speak - Talk with your machine in this minimalistic Rust crate!

tch-rs - Rust bindings for the C++ api of PyTorch.

FlexGen - Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput generation. [Moved to: https://github.com/FMInference/FlexGen]

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]

are-we-learning-yet - How ready is Rust for Machine Learning?

burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

ggml - Tensor library for machine learning

hora - 🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .

lightseq - LightSeq: A High Performance Library for Sequence Processing and Generation