ane-snowflake-arctic-embed-s/cosim.mlmodelc/model.mil

program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3304.6.1"}, {"coremlc-version", "3304.7.1"}, {"coremltools-component-torch", "2.1.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.2"}})]
{
    func main<ios17>(tensor<fp16, [?, 384]> files, tensor<fp16, [1, 384]> query) [FlexibleShapeInformation = tuple<tuple<tensor<string, []>, dict<tensor<string, []>, tensor<int32, [?]>>>, tuple<tensor<string, []>, dict<tensor<string, []>, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"files", [1, 384]}}), ("RangeDims", {{"files", [[1, 65536], [384, 384]]}})))] {
            tensor<bool, []> matmul_0_transpose_x_1 = const()[name = tensor<string, []>("matmul_0_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> matmul_0_transpose_y_1 = const()[name = tensor<string, []>("matmul_0_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, ?]> outputs = matmul(transpose_x = matmul_0_transpose_x_1, transpose_y = matmul_0_transpose_y_1, x = query, y = files)[name = tensor<string, []>("matmul_0_cast_fp16")];
        } -> (outputs);
}