Inference LLaMA models using CPU only

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

In a conda env with pytorch / cuda available, run

pip install -r requirements.txt

Then in this repository

pip install -e .

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

Model Card

See MODEL_CARD.md

License

See the LICENSE file.

CPU Inference

Place tokenizer.model and tokenizer_checklist.chk into /tokenizer folder

Place three files of 7B model into /model folder

Run python example-cpu.py