flake
llama.cpp
| flake | llama.cpp | |
|---|---|---|
| 5 | 775 | |
| 593 | 57,463 | |
| 3.9% | - | |
| 4.4 | 10.0 | |
| 7 days ago | 4 days ago | |
| Nix | C++ | |
| GNU Affero General Public License v3.0 | MIT License |
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flake
- Running AI Models on NixOS
- Nixified.Ai Release 2
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Llama.cpp: Full CUDA GPU Acceleration
> Ideally, there's Nix (and poetry2nix) that could take care of everything, but only a few folks write Flakes for their projects.
Relevant to "AI, Python, setting up is hard ... nix", there's stuff like:
https://github.com/nixified-ai/flake
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Can you substitute conda with Nix for Data Science and ML/AI?
However, I would reach out to the Nixified.ai folks about it, because I can see that the invoke.ai build script mentions pytorch and several other hard-to-install packages (albeit not detectron).
- A Nix flake for many AI projects
llama.cpp
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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
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Embeddings are a good starting point for the AI curious app developer
Have just done this recently for local chat with pdf feature in https://recurse.chat. (It's a macOS app that has built-in llama.cpp server and local vector database)
Running an embedding server locally is pretty straightforward:
- Get llama.cpp release binary: https://github.com/ggerganov/llama.cpp/releases
What are some alternatives?
nonguix - Nonguix mirror – pull requests ignored, please use upstream for that
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
guix-nonfree - Unofficial collection of packages that are not going to be accepted in to guix
gpt4all - gpt4all: run open-source LLMs anywhere
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.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
llama_cpp.rb - llama_cpp provides Ruby bindings for llama.cpp
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
serving - A flexible, high-performance serving system for machine learning models
ggml - Tensor library for machine learning
guix-nonfree
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM