def METHOD_NAME(self, config_or_num_layers: Union[dict, int] = None) -> List[StateDictNameMapping]:
    num_layer = self.resolve_num_layer(config_or_num_layers)
    mappings = [
        ["embeddings.word_embeddings.weight", "embeddings.word_embeddings.weight"],
        ["embeddings.position_embeddings.weight", "embeddings.position_embeddings.weight"],
        ["embeddings.token_type_embeddings.weight", "embeddings.token_type_embeddings.weight"],
        ["embeddings.LayerNorm.weight", "embeddings.layer_norm.weight"],
        ["embeddings.LayerNorm.bias", "embeddings.layer_norm.bias"],
        ["pooler.dense.weight", "pooler.dense.weight", "transpose"],
        ["pooler.dense.bias", "pooler.dense.bias"],
    ]
    for layer_index in range(num_layer):
        layer_mappings = [
            [
                f"encoder.layer.{layer_index}.attention.self.query.weight",
                f"encoder.layers.{layer_index}.self_attn.q_proj.weight",
                "transpose",
            ],
            [
                f"encoder.layer.{layer_index}.attention.self.query.bias",
                f"encoder.layers.{layer_index}.self_attn.q_proj.bias",
            ],
            [
                f"encoder.layer.{layer_index}.attention.self.key.weight",
                f"encoder.layers.{layer_index}.self_attn.k_proj.weight",
                "transpose",
            ],
            [
                f"encoder.layer.{layer_index}.attention.self.key.bias",
                f"encoder.layers.{layer_index}.self_attn.k_proj.bias",
            ],
            [
                f"encoder.layer.{layer_index}.attention.self.value.weight",
                f"encoder.layers.{layer_index}.self_attn.v_proj.weight",
                "transpose",
            ],
            [
                f"encoder.layer.{layer_index}.attention.self.value.bias",
                f"encoder.layers.{layer_index}.self_attn.v_proj.bias",
            ],
            [
                f"encoder.layer.{layer_index}.attention.output.dense.weight",
                f"encoder.layers.{layer_index}.self_attn.out_proj.weight",
                "transpose",
            ],
            [
                f"encoder.layer.{layer_index}.attention.output.dense.bias",
                f"encoder.layers.{layer_index}.self_attn.out_proj.bias",
            ],
            [
                f"encoder.layer.{layer_index}.attention.output.LayerNorm.weight",
                f"encoder.layers.{layer_index}.norm1.weight",
            ],
            [
                f"encoder.layer.{layer_index}.attention.output.LayerNorm.bias",
                f"encoder.layers.{layer_index}.norm1.bias",
            ],
            [
                f"encoder.layer.{layer_index}.intermediate.dense.weight",
                f"encoder.layers.{layer_index}.linear1.weight",
                "transpose",
            ],
            [f"encoder.layer.{layer_index}.intermediate.dense.bias", f"encoder.layers.{layer_index}.linear1.bias"],
            [
                f"encoder.layer.{layer_index}.output.dense.weight",
                f"encoder.layers.{layer_index}.linear2.weight",
                "transpose",
            ],
            [f"encoder.layer.{layer_index}.output.dense.bias", f"encoder.layers.{layer_index}.linear2.bias"],
            [f"encoder.layer.{layer_index}.output.LayerNorm.weight", f"encoder.layers.{layer_index}.norm2.weight"],
            [f"encoder.layer.{layer_index}.output.LayerNorm.bias", f"encoder.layers.{layer_index}.norm2.bias"],
        ]
        mappings.extend(layer_mappings)
    return [StateDictNameMapping(*mapping) for mapping in mappings]