""" | |
CLI to run merge a trained LoRA into a base model | |
""" | |
from pathlib import Path | |
import fire | |
import transformers | |
from axolotl.cli import do_merge_lora, load_cfg, print_axolotl_text_art | |
from axolotl.common.cli import TrainerCliArgs | |
def do_cli(config: Path = Path("examples/"), **kwargs): | |
# pylint: disable=duplicate-code | |
print_axolotl_text_art() | |
parser = transformers.HfArgumentParser((TrainerCliArgs)) | |
parsed_cli_args, _ = parser.parse_args_into_dataclasses( | |
return_remaining_strings=True | |
) | |
parsed_cli_args.merge_lora = True | |
parsed_cfg = load_cfg( | |
config, | |
merge_lora=True, | |
load_in_8bit=False, | |
load_in_4bit=False, | |
flash_attention=False, | |
**kwargs, | |
) | |
if not parsed_cfg.lora_model_dir and parsed_cfg.output_dir: | |
parsed_cfg.lora_model_dir = parsed_cfg.output_dir | |
if not Path(parsed_cfg.lora_model_dir).exists(): | |
raise ValueError( | |
f"Target directory for merge: `{parsed_cfg.lora_model_dir}` does not exist." | |
) | |
parsed_cfg.load_in_4bit = False | |
parsed_cfg.load_in_8bit = False | |
parsed_cfg.flash_attention = False | |
do_merge_lora(cfg=parsed_cfg, cli_args=parsed_cli_args) | |
if __name__ == "__main__": | |
fire.Fire(do_cli) | |