gemma.cpp
llama.cpp
| gemma.cpp | llama.cpp | |
|---|---|---|
| 8 | 791 | |
| 5,600 | 59,389 | |
| 2.2% | - | |
| 9.3 | 10.0 | |
| 7 days ago | 3 days ago | |
| C++ | C++ | |
| Apache License 2.0 | MIT License |
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gemma.cpp
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LLaMA Now Goes Faster on CPUs
For C++, also check out our https://github.com/google/gemma.cpp/blob/main/gemma.cc, which has direct calls to MatVec.
- FLaNK Stack 26 February 2024
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Gemma.cpp: lightweight, standalone C++ inference engine for Gemma models
Looks like they're working on it: https://github.com/google/gemma.cpp/issues/16
- Source code of Google Gemma model in C++
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Gemma: New Open Models
They have implemented the model also on their own C++ inference engine: https://github.com/google/gemma.cpp
llama.cpp
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
llamafile - Distribute and run LLMs with a single file.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
mud-pi - A simple MUD server in Python, for teaching purposes, which could be run on a Raspberry Pi
gpt4all - gpt4all: run open-source LLMs anywhere
gemma_pytorch - The official PyTorch implementation of Google's Gemma models
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
gemma - Open weights LLM from Google DeepMind.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
xpk - xpk (Accelerated Processing Kit, pronounced x-p-k,) is a software tool to help Cloud developers to orchestrate training jobs on accelerators such as TPUs and GPUs on GKE.
ggml - Tensor library for machine learning
htmx - </> htmx - high power tools for HTML
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM