aime-labs / llama-chat

Inference code for LLaMA models with chat extension

LLaMA

This repository is intended as a minimal, hackable and readable example to load LLaMA (arXiv) models and run inference. In order to download the checkpoints and tokenizer, fill this google form

Setup with AIME MLC

Create an AIME ML container: mlc-create mycontainer Pytorch 2.1.0-aime Once done open the container with: mlc-open mycontainer Navigate to the destination of the repo and install the required pip packages

cd llama-chat
pip install -r requirements.txt

Start Chat in Command Line

Run the chat mode in the command line with following command:

torchrun --nproc_per_node <num_gpus> chat.py --ckpt_dir <destination_of_checkpoints>

Download

Once your request is approved, you will receive links to download the tokenizer and model files. Edit the download.sh script with the signed url provided in the email to download the model weights and tokenizer.

Inference

The provided example.py can be run on a single or multi-gpu node with torchrun and will output completions for two pre-defined prompts. Using TARGET_FOLDER as defined in download.sh:

torchrun --nproc_per_node MP example.py --ckpt_dir $TARGET_FOLDER/model_size --tokenizer_path $TARGET_FOLDER/tokenizer.model

Different models require different MP values:

Model	MP
7B	1
13B	2
33B	4
65B	8

FAQ

• 1. The download.sh script doesn't work on default bash in MacOS X
• 2. Generations are bad!
• 3. CUDA Out of memory errors
• 4. Other languages

Reference

LLaMA: Open and Efficient Foundation Language Models -- https://arxiv.org/abs/2302.13971

@article{touvron2023llama,
  title={LLaMA: Open and Efficient Foundation Language Models},
  author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and Rodriguez, Aurelien and Joulin, Armand and Grave, Edouard and Lample, Guillaume},
  journal={arXiv preprint arXiv:2302.13971},
  year={2023}
}

Model Card

See MODEL_CARD.md

License

See the LICENSE file.