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
In a conda env with pytorch / cuda available, run
pip install -r requirements.txt
Then in this repository
pip install -e .
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.
The provided example.py can be run on a single gpu (as shown below) and will output completions for two pre-defined prompts. Using TARGET_FOLDER as defined in download.sh:
python example.py --ckpt_dir $TARGET_FOLDER/7B/ --tokenizer_path $TARGET_FOLDER/tokenizer.model
- 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
See MODEL_CARD.md
See the LICENSE file.