llm: a Rust crate/CLI for CPU inference of LLMs, including LLaMA, GPT-NeoX, GPT-J and more

This page summarizes the projects mentioned and recommended in the original post on /r/rust

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  • llm

    An ecosystem of Rust libraries for working with large language models

    We're looking for feedback on the project, and we'd love to hear from you! If you're interested in contributing, please reach out to us on our Discord, or post an issue on our GitHub.

  • ggml

    Tensor library for machine learning

    The current direction most people are taking is to "fine-tune" an existing base model (something like StableLM or Dolly) using a technique called LoRA. Ref: https://github.com/tloen/alpaca-lora People are also looking into fine-tuning directly on the GGML format. Ref: https://github.com/ggerganov/ggml/issues/8

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  • llama.cpp

    Port of Facebook's LLaMA model in C/C++

    At present, we are powered by ggml (similar to llama.cpp), but we intend to add additional backends in the near-future. This means that we currently only support CPU inference, but we have several ideas in mind for how to add GPU support, as well as other accelerators.

  • alpaca-lora

    Instruct-tune LLaMA on consumer hardware

    The current direction most people are taking is to "fine-tune" an existing base model (something like StableLM or Dolly) using a technique called LoRA. Ref: https://github.com/tloen/alpaca-lora People are also looking into fine-tuning directly on the GGML format. Ref: https://github.com/ggerganov/ggml/issues/8

  • tch-rs

    Rust bindings for the C++ api of PyTorch.

    You could try looking at the min-GPT example of tch-rs. I'd also strongly suggest watching Karpathy's video to understand what's going on.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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