def METHOD_NAME(
    model_tuned,
    model_org,
    save_to,
    save_precision,
    dim,
    v2,
    sdxl,
    conv_dim,
    clamp_quantile,
    min_diff,
    device,
):
    # Check for caption_text_input
    if model_tuned == '':
        log.info('Invalid finetuned model file')
        return
    if model_org == '':
        log.info('Invalid base model file')
        return
    # Check if source model exist
    if not os.path.isfile(model_tuned):
        log.info('The provided finetuned model is not a file')
        return
    if not os.path.isfile(model_org):
        log.info('The provided base model is not a file')
        return
    if not is_file_writable(save_to):
        return
    run_cmd = (
        f'{PYTHON} "{os.path.join("networks","extract_lora_from_models.py")}"'
    )
    run_cmd += f' --save_precision {save_precision}'
    run_cmd += f' --save_to "{save_to}"'
    run_cmd += f' --model_org "{model_org}"'
    run_cmd += f' --model_tuned "{model_tuned}"'
    run_cmd += f' --dim {dim}'
    run_cmd += f' --device {device}'
    if conv_dim > 0:
        run_cmd += f' --conv_dim {conv_dim}'
    if v2:
        run_cmd += f' --v2'
    if sdxl:
        run_cmd += f' --sdxl'
    run_cmd += f' --clamp_quantile {clamp_quantile}'
    run_cmd += f' --min_diff {min_diff}'
    log.info(run_cmd)
    # Run the command
    if os.name == 'posix':
        os.system(run_cmd)
    else:
        subprocess.run(run_cmd)