mlx-examples/llama
2023-11-29 10:38:20 -08:00
..
convert.py Add the Llama and Stable Diffusion examples 2023-11-29 10:38:20 -08:00
llama.py Add the Llama and Stable Diffusion examples 2023-11-29 10:38:20 -08:00
README.md Add the Llama and Stable Diffusion examples 2023-11-29 10:38:20 -08:00
requirements.txt Add the Llama and Stable Diffusion examples 2023-11-29 10:38:20 -08:00
sample_prompt.txt Add the Llama and Stable Diffusion examples 2023-11-29 10:38:20 -08:00

LLaMA

An example of generating text with LLaMA using MLX.

LLaMA is a set of open source language models from Meta AI Research1 ranging from 7B to 65B parameters.

Setup

Install the dependencies:

pip install -r requirements.txt

Next, download and convert the model. If you do not have access to the model weights you will need to request access from Meta.

Convert the weights with:

python convert.py <path_to_torch_weights> mlx_llama_weights.npz

Run

Once you've converted the weights to MLX format, you can interact with the LLaMA model:

python llama.py mlx_llama.npz tokenizer.model "hello"

Run python llama.py --help for more details.


  1. Refer to the arXiv paper and blog post for more details. ↩︎