LLMs on your local Computer (Part 1)

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • ggml

    Tensor library for machine learning

  • git clone https://github.com/ggerganov/ggml cd ggml mkdir build cd build cmake .. make -j4 gpt-j ../examples/gpt-j/download-ggml-model.sh 6B

  • llama.cpp

    LLM inference in C/C++

  • git clone --depth=1 https://github.com/ggerganov/llama.cpp cd llama.cpp mkdir build cd build cmake .. cmake --build . --config Release wget -c --show-progress -o models/llama-2-13b.Q4_0.gguf https://huggingface.co/TheBloke/Llama-2-13B-GGUF/resolve/main/llama-2-13b.Q4_0.gguf?download=true

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  • ollama

    Discontinued Get up and running with Llama 2, Mistral, Gemma, and other large language models. [Moved to: https://github.com/ollama/ollama] (by jmorganca)

  • ollama.ai

  • lit-gpt

    Discontinued Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. [Moved to: https://github.com/Lightning-AI/litgpt]

  • git clone --depth=1 https://github.com/Lightning-AI/lit-gpt cd lit-gpt pip install -r requirements.txt pip install bitsandbytes==0.41.0 huggingface_hub python scripts/download.py --repo_id stabilityai/stablelm-zephyr-3b --from_safetensors=True python scripts/convert_hf_checkpoint.py --checkpoint_dir checkpoints/stabilityai/stablelm-zephyr-3b --dtype float32

  • FastChat

    An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

  • FastChat

  • whisper.cpp

    Port of OpenAI's Whisper model in C/C++

  • The ggml library is one of the first library for local LLM interference. It’s a pure C library that converts models to run on several devices, including desktops, laptops, and even mobile device - and therefore, it can also be considered as a tinkering tool, trying new optimizations, that will then be incorporated into other downstream projects. This tool is at the heart of several other projects, powering LLM interference on desktop or even mobile phones. Subprojects for running specific LLMs or LLM families exists, such as whisper.cpp.

  • lit-llama

    Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

  • A pure Python library for running several open source LLMs locally, such as Mistral or StableLM. It also branched into subprojects for supporting specific LLM model-families, such as lit-llama. The projects goal are simplicity and optimization to run on several hardware. When used with 4bit quantization, it needs below 1GB to run a 3B model, and also CPU usage remains low.

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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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