llava

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