def PPHGNetV2_B6(pretrained=False, use_ssld=False, **kwargs):
    """
    PPHGNetV2_B6
    Args:
        pretrained (bool/str): If `True` load pretrained parameters, `False` otherwise.
                    If str, means the path of the pretrained model.
        use_ssld (bool) Whether using ssld pretrained model when pretrained is True.
    Returns:
        model: nn.Module. Specific `PPHGNetV2_B6` model depends on args.
    """
    stage_config = {
        # in_channels, mid_channels, out_channels, num_blocks, is_downsample, light_block, kernel_size, layer_num
        "stage1": [96, 96, 192, 2, False, False, 3, 6],
        "stage2": [192, 192, 512, 3, True, False, 3, 6],
        "stage3": [512, 384, 1024, 6, True, True, 5, 6],
        "stage4": [1024, 768, 2048, 3, True, True, 5, 6],
    }

    model = PPHGNetV2(
        stem_channels=[3, 48, 96], stage_config=stage_config, use_lab=False, **kwargs
    )
    return model

    PPHGNetV2_B6
    Args:
        pretrained (bool/str): If `True` load pretrained parameters, `False` otherwise.
                    If str, means the path of the pretrained model.
        use_ssld (bool) Whether using ssld pretrained model when pretrained is True.
    Returns:
        model: nn.Module. Specific `PPHGNetV2_B6` model depends on args.
    
pytorchocr/modeling/backbones/rec_pphgnetv2.py