rust-bert VS FlexGen

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


Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput generation. [Moved to:] (by Ying1123)
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rust-bert FlexGen
7 19
2,448 5,350
- -
5.8 10.0
9 days ago over 1 year ago
Rust Python
Apache License 2.0 Apache License 2.0
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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 cd rust-bert ORT_STRATEGY=system cargo run --example sentence_embeddings
  • Transformers.js
    9 projects | | 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 - 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 ( 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.


  • Running large language models like ChatGPT on a single GPU
    7 projects | | 20 Feb 2023
    Give this a look:

    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 | | 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.


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

    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 | | 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.


  • [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


Posts with mentions or reviews of FlexGen. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-16.

What are some alternatives?

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

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

text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.

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

CTranslate2 - Fast inference engine for Transformer models

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

ggml - Tensor library for machine learning

accelerate - 🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

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

stanford_alpaca - Code and documentation to train Stanford's Alpaca models, and generate the data.

tokenizers - 💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.