use type of A to compute, rather than hardcode fp16

src/frontends/onnx/frontend/src/op/com.microsoft/matmulnbits.cpp

@@ -169,12 +169,12 @@ ov::OutputVector matmulnbits(const ov::frontend::onnx::Node& node) {
         // use fp16 for compute
 
         // convert b to fp16
-        auto converted_b = std::make_shared<v0::Convert>(casted_b, ov::element::f16);
-        auto converted_zero_points = std::make_shared<v0::Convert>(zero_points, ov::element::f16);
+        auto converted_b = std::make_shared<v0::Convert>(casted_b, a.get_element_type());
+        auto converted_zero_points = std::make_shared<v0::Convert>(zero_points, a.get_element_type());
 
         // sub and scale
         const auto sub_b = std::make_shared<v1::Subtract>(converted_b, converted_zero_points);
-        const auto scales_fp16 = std::make_shared<v0::Convert>(scales, ov::element::f16);
+        const auto scales_fp16 = std::make_shared<v0::Convert>(scales, a.get_element_type());
         const auto scales_reshaped =
             op::util::reshape(scales_fp16, ov::Shape{static_cast<size_t>(N), static_cast<size_t>(n_blocks_per_col), 1});
         const auto scaled_b = std::make_shared<v1::Multiply>(sub_b, scales_reshaped);
@@ -198,9 +198,7 @@ ov::OutputVector matmulnbits(const ov::frontend::onnx::Node& node) {
         }
 
         // mm = matmul(a,b)
-        auto a_fp16 = std::make_shared<v0::Convert>(a, ov::element::f16);
-        auto results = std::make_shared<v0::MatMul>(a_fp16, b, false, true);
-        mm_output = std::make_shared<v0::Convert>(results, a.get_element_type());
+        mm_output = std::make_shared<v0::MatMul>(a, b, false, true);
     }
 
     if (bias.get_node_shared_ptr()) {
@@ -216,4 +214,4 @@ ONNX_OP("MatMulNBits", OPSET_SINCE(1), com_microsoft::opset_1::matmulnbits, MICR
 }  // namespace com_microsoft
 }  // namespace onnx
 }  // namespace frontend
-}  // namespace ov
+}  // namespace ov