Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

PyTorch Nightlies

If you want to use PyTorch nightlies instead of the stable release, go to this guide to retrieve the right --extra-index-url URL parameter for the pip install commands on your platform.

Installing

Llama-recipes provides a pip distribution for easy install and usage in other projects. Alternatively, it can be installed from source.

Install with pip

pip install llama-recipes

Install with optional dependencies

Llama-recipes offers the installation of optional packages. There are three optional dependency groups. To run the unit tests we can install the required dependencies with:

pip install llama-recipes[tests]

For the vLLM example we need additional requirements that can be installed with:

pip install llama-recipes[vllm]

To use the sensitive topics safety checker install with:

pip install llama-recipes[auditnlg]

Some recipes require the presence of langchain. To install the packages follow the recipe description or install with:

pip install llama-recipes[langchain]

Optional dependencies can also be combined with [option1,option2].

Install from source

To install from source e.g. for development use these commands. We're using hatchling as our build backend which requires an up-to-date pip as well as setuptools package.

git clone git@github.com:meta-llama/llama-recipes.git
cd llama-recipes
pip install -U pip setuptools
pip install -e .

For development and contributing to llama-recipes please install all optional dependencies:

git clone git@github.com:meta-llama/llama-recipes.git
cd llama-recipes
pip install -U pip setuptools
pip install -e .[tests,auditnlg,vllm]

Getting the Llama models

You can find Llama models on Hugging Face hub here, where models with hf in the name are already converted to Hugging Face checkpoints so no further conversion is needed. The conversion step below is only for original model weights from Meta that are hosted on Hugging Face model hub as well.

Model conversion to Hugging Face

If you have the model checkpoints downloaded from the Meta website, you can convert it to the Hugging Face format with:

## Install Hugging Face Transformers from source
pip freeze | grep transformers ## verify it is version 4.45.0 or higher

git clone git@github.com:huggingface/transformers.git
cd transformers
pip install protobuf
python src/transformers/models/llama/convert_llama_weights_to_hf.py \
   --input_dir /path/to/downloaded/llama/weights --model_size 3B --output_dir /output/path