ggml

Tensor library for machine learning (by ggerganov)

Ggml Alternatives

Similar projects and alternatives to ggml

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better ggml alternative or higher similarity.

ggml reviews and mentions

Posts with mentions or reviews of ggml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-11.
  • LLMs on your local Computer (Part 1)
    7 projects | dev.to | 11 Mar 2024
    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
  • GGUF, the Long Way Around
    2 projects | news.ycombinator.com | 29 Feb 2024
    Cool. I was just learning about GGUF by creating my own parser for it based on the spec https://github.com/ggerganov/ggml/blob/master/docs/gguf.md (for educational purposes)
  • Ask HN: People who switched from GPT to their own models. How was it?
    3 projects | news.ycombinator.com | 26 Feb 2024
    If you don't care about the details of how those model servers work, then something that abstracts out the whole process like LM Studio or Ollama is all you need.

    However, if you want to get into the weeds of how this actually works, I recommend you look up model quantization and some libraries like ggml[1] that actually do that for you.

    [1] https://github.com/ggerganov/ggml

  • GGUF File Format
    1 project | news.ycombinator.com | 31 Dec 2023
  • Google just shipped libggml from llama-cpp into its Android AICore
    2 projects | /r/LocalLLaMA | 9 Dec 2023
    Because the library is called ggml, but it supports gguf.
  • Q-Transformer
    2 projects | news.ycombinator.com | 30 Nov 2023
    Apparently this guy like a bunch of others like https://github.com/ggerganov/ggml are implementing transformers from papers for people that want them. Pretty cool.
  • [P] Inference Vision Transformer (ViT) in plain C/C++ with ggml
    2 projects | /r/MachineLearning | 26 Nov 2023
    You can access it here: https://github.com/staghado/vit.cpp It has been added to the ggml library on GitHub: https://github.com/ggerganov/ggml
  • Falcon 180B Released
    1 project | news.ycombinator.com | 6 Sep 2023
    https://github.com/ggerganov/ggml

    One note is that prompt ingestion is extremely slow on CPU compared to GPU. So short prompts are fine (as tokens can be streamed once the prompt is ingested), but long prompts feel extremely sluggish.

  • Stable Diffusion in pure C/C++
    8 projects | news.ycombinator.com | 19 Aug 2023
    I did a quick run under profiler and on my AVX2-laptop the slowest part (>50%) was matrix multiplication (sgemm).

    In current version of GGML if OpenBLAS is enabled, they convert matrices to FP32 before running sgemm.

    If OpenBLAS is disabled, on AVX2 plaftorm they convert FP16 to FP32 on every FMA operation, which even worse (due to repetition). After that, both ggml_vec_dot_f16 and ggml_vec_dot_f32 took first place in profiler.

    Source: https://github.com/ggerganov/ggml/blob/master/src/ggml.c#L10...

  • Accessing Llama 2 from the command-line with the LLM-replicate plugin
    16 projects | news.ycombinator.com | 18 Jul 2023
    For those getting started, the easiest one click installer I've used is Nomic.ai's gpt4all: https://gpt4all.io/

    This runs with a simple GUI on Windows/Mac/Linux, leverages a fork of llama.cpp on the backend and supports GPU acceleration, and LLaMA, Falcon, MPT, and GPT-J models. It also has API/CLI bindings.

    I just saw a slick new tool https://ollama.ai/ that will let you install a llama2-7b with a single `ollama run llama2` command that has a very simple 1-click installer for Apple Silicon Mac (but need to build from source for anything else atm). It looks like it only supports llamas OOTB but it also seems to use llama.cpp (via Go adapter) on the backend - it seemed to be CPU-only on my MBA, but I didn't poke too much and it's brand new, so we'll see.

    For anyone on HN, they should probably be looking at https://github.com/ggerganov/llama.cpp and https://github.com/ggerganov/ggml directly. If you have a high-end Nvidia consumer card (3090/4090) I'd highly recommend looking into https://github.com/turboderp/exllama

    For those generally confused, the r/LocalLLaMA wiki is a good place to start: https://www.reddit.com/r/LocalLLaMA/wiki/guide/

    I've also been porting my own notes into a single location that tracks models, evals, and has guides focused on local models: https://llm-tracker.info/

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Stats

Basic ggml repo stats
69
9,642
9.8
1 day ago

ggerganov/ggml is an open source project licensed under MIT License which is an OSI approved license.

The primary programming language of ggml is C.


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