Load weights issues

[MaoShanhunzi]

When I load Slak-T,Slak-s,Slak-b's pre-trained model on imagenet1k the following error is reported. What's the reason, please?

RuntimeError: Error(s) in loading state_dict for SLaK:
Missing key(s) in state_dict: "downsample_layers.0.0.weight", "downsample_layers.0.0.bias", "downsample_layers.0.1.weight", "downsample_layers.0.1.bias", "downsample_layers.1.0.weight", "downsample_layers.1.0.bias", "downsample_layers.1.1.weight", "downsample_layers.1.1.bias", "downsample_layers.2.0.weight", "downsample_layers.2.0.bias", "downsample_layers.2.1.weight", "downsample_layers.2.1.bias", "downsample_layers.3.0.weight", "downsample_layers.3.0.bias", "downsample_layers.3.1.weight", "downsample_layers.3.1.bias", "stages.0.0.gamma", "stages.0.0.large_kernel.lkb_origin.conv.weight", "stages.0.0.large_kernel.lkb_origin.bn.weight", "stages.0.0.large_kernel.lkb_origin.bn.bias", "stages.0.0.large_kernel.lkb_origin.bn.running_mean", "stages.0.0.large_kernel.lkb_origin.bn.running_var", "stages.0.0.large_kernel.small_conv.conv.weight", "stages.0.0.large_kernel.small_conv.bn.weight", "stages.0.0.large_kernel.small_conv.bn.bias", "stages.0.0.large_kernel.small_conv.bn.running_mean", "stages.0.0.large_kernel.small_conv.bn.running_var", "stages.0.0.norm.weight", "stages.0.0.norm.bias", "stages.0.0.pwconv1.weight", "stages.0.0.pwconv1.bias", "stages.0.0.pwconv2.weight", "stages.0.0.pwconv2.bias", "stages.0.1.gamma", "stages.0.1.large_kernel.lkb_origin.conv.weight", "stages.0.1.large_kernel.lkb_origin.bn.weight", "stages.0.1.large_kernel.lkb_origin.bn.bias", "stages.0.1.large_kernel.lkb_origin.bn.running_mean", "stages.0.1.large_kernel.lkb_origin.bn.running_var", "stages.0.1.large_kernel.small_conv.conv.weight", "stages.0.1.large_kernel.small_conv.bn.weight", "stages.0.1.large_kernel.small_conv.bn.bias", "stages.0.1.large_kernel.small_conv.bn.running_mean", "stages.0.1.large_kernel.small_conv.bn.running_var", "stages.0.1.norm.weight", "stages.0.1.norm.bias", "stages.0.1.pwconv1.weight", "stages.0.1.pwconv1.bias", "stages.0.1.pwconv2.weight", "stages.0.1.pwconv2.bias", "stages.0.2.gamma", "stages.0.2.large_kernel.lkb_origin.conv.weight", "stages.0.2.large_kernel.lkb_origin.bn.weight", "stages.0.2.large_kernel.lkb_origin.bn.bias", "stages.0.2.large_kernel.lkb_origin.bn.running_mean", "stages.0.2.large_kernel.lkb_origin.bn.running_var", "stages.0.2.large_kernel.small_conv.conv.weight", "stages.0.2.large_kernel.small_conv.bn.weight", "stages.0.2.large_kernel.small_conv.bn.bias", "stages.0.2.large_kernel.small_conv.bn.running_mean", "stages.0.2.large_kernel.small_conv.bn.running_var", "stages.0.2.norm.weight", "stages.0.2.norm.bias", "stages.0.2.pwconv1.weight", "stages.0.2.pwconv1.bias", "stages.0.2.pwconv2.weight", "stages.0.2.pwconv2.bias", "stages.1.0.gamma", "stages.1.0.large_kernel.lkb_origin.conv.weight", "stages.1.0.large_kernel.lkb_origin.bn.weight", "stages.1.0.large_kernel.lkb_origin.bn.bias", "stages.1.0.large_kernel.lkb_origin.bn.running_mean", "stages.1.0.large_kernel.lkb_origin.bn.running_var", "stages.1.0.large_kernel.small_conv.conv.weight", "stages.1.0.large_kernel.small_conv.bn.weight", "stages.1.0.large_kernel.small_conv.bn.bias", "stages.1.0.large_kernel.small_conv.bn.running_mean", "stages.1.0.large_kernel.small_conv.bn.running_var", "stages.1.0.norm.weight", "stages.1.0.norm.bias", "stages.1.0.pwconv1.weight", "stages.1.0.pwconv1.bias", "stages.1.0.pwconv2.weight", "stages.1.0.pwconv2.bias", "stages.1.1.gamma", "stages.1.1.large_kernel.lkb_origin.conv.weight", "stages.1.1.large_kernel.lkb_origin.bn.weight", "stages.1.1.large_kernel.lkb_origin.bn.bias", "stages.1.1.large_kernel.lkb_origin.bn.running_mean", "stages.1.1.large_kernel.lkb_origin.bn.running_var",
......
Unexpected key(s) in state_dict: "model", "optimizer", "epoch", "scaler", "args", "model_ema".