def METHOD_NAME(onnx_model: onnx.ModelProto):
    """
    See variant 3 in docstring of transform
    """
    # add in bias
    bias = helper.make_tensor("bias", onnx.TensorProto.FLOAT, (1,), [1])
    gemm = [n for n in onnx_model.graph.node if n.op_type == "Gemm"][0]
    gemm.input.append("bias")
    onnx_model.graph.initializer.append(bias)
    # add in dequant after the output quant node
    onnx_model.graph.node.append(
        helper.make_node(
            "DequantizeLinear",
            ["output_quant_output", "y_scale"],
            ["output_dequant_output"],
            name="output_dequant",
        )
    )
    validate_onnx(onnx_model)
    onnx_model = GemmToQLinearMatMul().apply(onnx_model)
    validate_onnx(onnx_model)
    assert [i.name for i in onnx_model.graph.initializer] == [
        "x_scale",
        "y_scale",
        "zero_point",
        "bias",
        "gemm.weight_quantized",
    ]
    assert [n.name for n in onnx_model.graph.node] == [
        "gemm_quant",
        "output_dequant",
        "gemm_injected_bias_add",
    ]