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Running
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A10G
Running
on
A10G
File size: 767 Bytes
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import argparse
from llava.model.builder import load_pretrained_model
from llava.mm_utils import get_model_name_from_path
def merge_lora(args):
model_name = get_model_name_from_path(args.model_path)
tokenizer, model, image_processor, context_len = load_pretrained_model(args.model_path, args.model_base, model_name, device_map='cpu')
model.save_pretrained(args.save_model_path)
tokenizer.save_pretrained(args.save_model_path)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--model-path", type=str, required=True)
parser.add_argument("--model-base", type=str, required=True)
parser.add_argument("--save-model-path", type=str, required=True)
args = parser.parse_args()
merge_lora(args)
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