llama2.rs
llama.cpp
| llama2.rs | llama.cpp | |
|---|---|---|
| 3 | 780 | |
| 981 | 58,425 | |
| - | - | |
| 8.9 | 10.0 | |
| 6 months ago | 3 days ago | |
| Rust | C++ | |
| MIT License | MIT License |
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llama2.rs
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Ask HN: Cheapest hardware to run Llama 2 70B
This code runs Llama2 quantized and unquantized in a roughly minimal way: https://github.com/srush/llama2.rs (though extracting the quantized 70B weights takes a lot of RAM). I'm running the 13B quantized model on ~10-11GB of CPU memory.
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Candle: Torch Replacement in Rust
Nowhere near as neat as candle or ggml, but just released a 4-bit rust llama2 implementation with simd. Runs pretty fast.
https://github.com/srush/llama2.rs/
- Llama2.rs: One-file Rust implementation of Llama2
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?
burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
candle - Minimalist ML framework for Rust
gpt4all - gpt4all: run open-source LLMs anywhere
euclid - Geometry primitives (basic linear algebra) for Rust
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
petals - 🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
ggml - Tensor library for machine learning
syntaxdot - Neural syntax annotator, supporting sequence labeling, lemmatization, and dependency parsing.
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM