| from opencompass.models import Llama2 | |
| # Please follow the instruction in the Meta AI website https://github.com/facebookresearch/llama/tree/llama_v1 | |
| # and download the LLaMA model and tokenizer to the path './models/llama/'. | |
| # | |
| # The LLaMA requirement is also needed to be installed. | |
| # *Note* that the LLaMA-2 branch is fully compatible with LLAMA-1, and the LLaMA-2 branch is used here. | |
| # | |
| # git clone https://github.com/facebookresearch/llama.git | |
| # cd llama | |
| # pip install -e . | |
| models = [ | |
| dict( | |
| abbr="llama-13b", | |
| type=Llama2, | |
| path="./models/llama/13B/", | |
| tokenizer_path="./models/llama/tokenizer.model", | |
| max_out_len=100, | |
| max_seq_len=2048, | |
| batch_size=16, | |
| run_cfg=dict(num_gpus=2, num_procs=2), | |
| ), | |
| ] | |