latin/560ms (shared Latin-script-prune model: en/es/fr/it/pt/de)

latin/560ms/decoder.mlmodelc/analytics/coremldata.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6a574ca5ab5cc407100f598e070db5d65086b3a2ed9edbd7c787a1ae7be7dcba
+size 243

latin/560ms/decoder.mlmodelc/coremldata.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed5dae3a122e9aa360897a62d7277e42ce99ec1930b105246c590940dcd3be1b
+size 433

latin/560ms/decoder.mlmodelc/model.mil

@@ -0,0 +1,64 @@
+program(1.3)
+[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})]
+{
+    func main<ios18>(tensor<fp32, [2, 1, 640]> c_in, tensor<fp32, [2, 1, 640]> h_in, tensor<int32, [1, 1]> token, tensor<int32, [1]> token_length) {
+            int32 y_axis_0 = const()[name = string("y_axis_0"), val = int32(0)];
+            int32 y_batch_dims_0 = const()[name = string("y_batch_dims_0"), val = int32(0)];
+            bool y_validate_indices_0 = const()[name = string("y_validate_indices_0"), val = bool(false)];
+            tensor<fp16, [2829, 640]> module_prediction_embed_weight_to_fp16 = const()[name = string("module_prediction_embed_weight_to_fp16"), val = tensor<fp16, [2829, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
+            string token_to_int16_dtype_0 = const()[name = string("token_to_int16_dtype_0"), val = string("int16")];
+            tensor<int16, [1, 1]> token_to_int16 = cast(dtype = token_to_int16_dtype_0, x = token)[name = string("cast_8")];
+            tensor<fp16, [1, 1, 640]> y_cast_fp16_cast_uint16 = gather(axis = y_axis_0, batch_dims = y_batch_dims_0, indices = token_to_int16, validate_indices = y_validate_indices_0, x = module_prediction_embed_weight_to_fp16)[name = string("y_cast_fp16_cast_uint16")];
+            tensor<int32, [3]> input_3_perm_0 = const()[name = string("input_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
+            int32 split_0_num_splits_0 = const()[name = string("split_0_num_splits_0"), val = int32(2)];
+            int32 split_0_axis_0 = const()[name = string("split_0_axis_0"), val = int32(0)];
+            string h_in_to_fp16_dtype_0 = const()[name = string("h_in_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [2, 1, 640]> h_in_to_fp16 = cast(dtype = h_in_to_fp16_dtype_0, x = h_in)[name = string("cast_7")];
+            tensor<fp16, [1, 1, 640]> split_0_cast_fp16_0, tensor<fp16, [1, 1, 640]> split_0_cast_fp16_1 = split(axis = split_0_axis_0, num_splits = split_0_num_splits_0, x = h_in_to_fp16)[name = string("split_0_cast_fp16")];
+            int32 split_1_num_splits_0 = const()[name = string("split_1_num_splits_0"), val = int32(2)];
+            int32 split_1_axis_0 = const()[name = string("split_1_axis_0"), val = int32(0)];
+            string c_in_to_fp16_dtype_0 = const()[name = string("c_in_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [2, 1, 640]> c_in_to_fp16 = cast(dtype = c_in_to_fp16_dtype_0, x = c_in)[name = string("cast_6")];
+            tensor<fp16, [1, 1, 640]> split_1_cast_fp16_0, tensor<fp16, [1, 1, 640]> split_1_cast_fp16_1 = split(axis = split_1_axis_0, num_splits = split_1_num_splits_0, x = c_in_to_fp16)[name = string("split_1_cast_fp16")];
+            tensor<int32, [1]> input_lstm_layer_0_lstm_h0_squeeze_axes_0 = const()[name = string("input_lstm_layer_0_lstm_h0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_lstm_layer_0_lstm_h0_squeeze_cast_fp16 = squeeze(axes = input_lstm_layer_0_lstm_h0_squeeze_axes_0, x = split_0_cast_fp16_0)[name = string("input_lstm_layer_0_lstm_h0_squeeze_cast_fp16")];
+            tensor<int32, [1]> input_lstm_layer_0_lstm_c0_squeeze_axes_0 = const()[name = string("input_lstm_layer_0_lstm_c0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_lstm_layer_0_lstm_c0_squeeze_cast_fp16 = squeeze(axes = input_lstm_layer_0_lstm_c0_squeeze_axes_0, x = split_1_cast_fp16_0)[name = string("input_lstm_layer_0_lstm_c0_squeeze_cast_fp16")];
+            string input_lstm_layer_0_direction_0 = const()[name = string("input_lstm_layer_0_direction_0"), val = string("forward")];
+            bool input_lstm_layer_0_output_sequence_0 = const()[name = string("input_lstm_layer_0_output_sequence_0"), val = bool(true)];
+            string input_lstm_layer_0_recurrent_activation_0 = const()[name = string("input_lstm_layer_0_recurrent_activation_0"), val = string("sigmoid")];
+            string input_lstm_layer_0_cell_activation_0 = const()[name = string("input_lstm_layer_0_cell_activation_0"), val = string("tanh")];
+            string input_lstm_layer_0_activation_0 = const()[name = string("input_lstm_layer_0_activation_0"), val = string("tanh")];
+            tensor<fp16, [2560, 640]> concat_1_to_fp16 = const()[name = string("concat_1_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3621248)))];
+            tensor<fp16, [2560, 640]> concat_2_to_fp16 = const()[name = string("concat_2_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898112)))];
+            tensor<fp16, [2560]> concat_0_to_fp16 = const()[name = string("concat_0_to_fp16"), val = tensor<fp16, [2560]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10174976)))];
+            tensor<fp16, [1, 1, 640]> input_3_cast_fp16 = transpose(perm = input_3_perm_0, x = y_cast_fp16_cast_uint16)[name = string("transpose_2")];
+            tensor<fp16, [1, 1, 640]> input_lstm_layer_0_cast_fp16_0, tensor<fp16, [1, 640]> input_lstm_layer_0_cast_fp16_1, tensor<fp16, [1, 640]> input_lstm_layer_0_cast_fp16_2 = lstm(activation = input_lstm_layer_0_activation_0, bias = concat_0_to_fp16, cell_activation = input_lstm_layer_0_cell_activation_0, direction = input_lstm_layer_0_direction_0, initial_c = input_lstm_layer_0_lstm_c0_squeeze_cast_fp16, initial_h = input_lstm_layer_0_lstm_h0_squeeze_cast_fp16, output_sequence = input_lstm_layer_0_output_sequence_0, recurrent_activation = input_lstm_layer_0_recurrent_activation_0, weight_hh = concat_2_to_fp16, weight_ih = concat_1_to_fp16, x = input_3_cast_fp16)[name = string("input_lstm_layer_0_cast_fp16")];
+            tensor<int32, [1]> input_lstm_h0_squeeze_axes_0 = const()[name = string("input_lstm_h0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_lstm_h0_squeeze_cast_fp16 = squeeze(axes = input_lstm_h0_squeeze_axes_0, x = split_0_cast_fp16_1)[name = string("input_lstm_h0_squeeze_cast_fp16")];
+            tensor<int32, [1]> input_lstm_c0_squeeze_axes_0 = const()[name = string("input_lstm_c0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_lstm_c0_squeeze_cast_fp16 = squeeze(axes = input_lstm_c0_squeeze_axes_0, x = split_1_cast_fp16_1)[name = string("input_lstm_c0_squeeze_cast_fp16")];
+            string input_direction_0 = const()[name = string("input_direction_0"), val = string("forward")];
+            bool input_output_sequence_0 = const()[name = string("input_output_sequence_0"), val = bool(true)];
+            string input_recurrent_activation_0 = const()[name = string("input_recurrent_activation_0"), val = string("sigmoid")];
+            string input_cell_activation_0 = const()[name = string("input_cell_activation_0"), val = string("tanh")];
+            string input_activation_0 = const()[name = string("input_activation_0"), val = string("tanh")];
+            tensor<fp16, [2560, 640]> concat_4_to_fp16 = const()[name = string("concat_4_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10180160)))];
+            tensor<fp16, [2560, 640]> concat_5_to_fp16 = const()[name = string("concat_5_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13457024)))];
+            tensor<fp16, [2560]> concat_3_to_fp16 = const()[name = string("concat_3_to_fp16"), val = tensor<fp16, [2560]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16733888)))];
+            tensor<fp16, [1, 1, 640]> input_cast_fp16_0, tensor<fp16, [1, 640]> input_cast_fp16_1, tensor<fp16, [1, 640]> input_cast_fp16_2 = lstm(activation = input_activation_0, bias = concat_3_to_fp16, cell_activation = input_cell_activation_0, direction = input_direction_0, initial_c = input_lstm_c0_squeeze_cast_fp16, initial_h = input_lstm_h0_squeeze_cast_fp16, output_sequence = input_output_sequence_0, recurrent_activation = input_recurrent_activation_0, weight_hh = concat_5_to_fp16, weight_ih = concat_4_to_fp16, x = input_lstm_layer_0_cast_fp16_0)[name = string("input_cast_fp16")];
+            int32 obj_3_axis_0 = const()[name = string("obj_3_axis_0"), val = int32(0)];
+            tensor<fp16, [2, 1, 640]> obj_3_cast_fp16 = stack(axis = obj_3_axis_0, values = (input_lstm_layer_0_cast_fp16_1, input_cast_fp16_1))[name = string("obj_3_cast_fp16")];
+            string obj_3_cast_fp16_to_fp32_dtype_0 = const()[name = string("obj_3_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            int32 obj_axis_0 = const()[name = string("obj_axis_0"), val = int32(0)];
+            tensor<fp16, [2, 1, 640]> obj_cast_fp16 = stack(axis = obj_axis_0, values = (input_lstm_layer_0_cast_fp16_2, input_cast_fp16_2))[name = string("obj_cast_fp16")];
+            string obj_cast_fp16_to_fp32_dtype_0 = const()[name = string("obj_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([1, 2, 0])];
+            string transpose_0_cast_fp16_to_fp32_dtype_0 = const()[name = string("transpose_0_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            tensor<fp16, [1, 640, 1]> transpose_0_cast_fp16 = transpose(perm = transpose_0_perm_0, x = input_cast_fp16_0)[name = string("transpose_1")];
+            tensor<fp32, [1, 640, 1]> decoder_out = cast(dtype = transpose_0_cast_fp16_to_fp32_dtype_0, x = transpose_0_cast_fp16)[name = string("cast_3")];
+            tensor<fp32, [2, 1, 640]> c_out = cast(dtype = obj_cast_fp16_to_fp32_dtype_0, x = obj_cast_fp16)[name = string("cast_4")];
+            tensor<fp32, [2, 1, 640]> h_out = cast(dtype = obj_3_cast_fp16_to_fp32_dtype_0, x = obj_3_cast_fp16)[name = string("cast_5")];
+            tensor<int32, [1]> token_length_tmp = identity(x = token_length)[name = string("token_length_tmp")];
+        } -> (decoder_out, h_out, c_out);
+}

latin/560ms/decoder.mlmodelc/weights/weight.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:923df635dad8f9688d46afdf1689c0913cc977f9944db30e35a78e5b41799903
+size 16739072

latin/560ms/decoder_joint.mlmodelc/analytics/coremldata.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3503c16cc1df6745efddcf09fec2ab879cbc105dca3844ec0bc43caf31f3b494
+size 243

latin/560ms/decoder_joint.mlmodelc/coremldata.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:57dab53e7102b3dbcb62136ca3cc677b8048990224ded6690ceb591fd671c948
+size 454

latin/560ms/decoder_joint.mlmodelc/model.mil

@@ -0,0 +1,83 @@
+program(1.3)
+[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})]
+{
+    func main<ios18>(tensor<fp32, [2, 1, 640]> c_in, tensor<fp32, [1, 1024, 1]> encoder, tensor<fp32, [2, 1, 640]> h_in, tensor<int32, [1, 1]> token, tensor<int32, [1]> token_length) {
+            int32 y_axis_0 = const()[name = string("y_axis_0"), val = int32(0)];
+            int32 y_batch_dims_0 = const()[name = string("y_batch_dims_0"), val = int32(0)];
+            bool y_validate_indices_0 = const()[name = string("y_validate_indices_0"), val = bool(false)];
+            tensor<fp16, [2829, 640]> decoder_module_prediction_embed_weight_to_fp16 = const()[name = string("decoder_module_prediction_embed_weight_to_fp16"), val = tensor<fp16, [2829, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
+            string token_to_int16_dtype_0 = const()[name = string("token_to_int16_dtype_0"), val = string("int16")];
+            tensor<int16, [1, 1]> token_to_int16 = cast(dtype = token_to_int16_dtype_0, x = token)[name = string("cast_9")];
+            tensor<fp16, [1, 1, 640]> y_cast_fp16_cast_uint16 = gather(axis = y_axis_0, batch_dims = y_batch_dims_0, indices = token_to_int16, validate_indices = y_validate_indices_0, x = decoder_module_prediction_embed_weight_to_fp16)[name = string("y_cast_fp16_cast_uint16")];
+            tensor<int32, [3]> input_3_perm_0 = const()[name = string("input_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
+            int32 split_0_num_splits_0 = const()[name = string("split_0_num_splits_0"), val = int32(2)];
+            int32 split_0_axis_0 = const()[name = string("split_0_axis_0"), val = int32(0)];
+            string h_in_to_fp16_dtype_0 = const()[name = string("h_in_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [2, 1, 640]> h_in_to_fp16 = cast(dtype = h_in_to_fp16_dtype_0, x = h_in)[name = string("cast_8")];
+            tensor<fp16, [1, 1, 640]> split_0_cast_fp16_0, tensor<fp16, [1, 1, 640]> split_0_cast_fp16_1 = split(axis = split_0_axis_0, num_splits = split_0_num_splits_0, x = h_in_to_fp16)[name = string("split_0_cast_fp16")];
+            int32 split_1_num_splits_0 = const()[name = string("split_1_num_splits_0"), val = int32(2)];
+            int32 split_1_axis_0 = const()[name = string("split_1_axis_0"), val = int32(0)];
+            string c_in_to_fp16_dtype_0 = const()[name = string("c_in_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [2, 1, 640]> c_in_to_fp16 = cast(dtype = c_in_to_fp16_dtype_0, x = c_in)[name = string("cast_7")];
+            tensor<fp16, [1, 1, 640]> split_1_cast_fp16_0, tensor<fp16, [1, 1, 640]> split_1_cast_fp16_1 = split(axis = split_1_axis_0, num_splits = split_1_num_splits_0, x = c_in_to_fp16)[name = string("split_1_cast_fp16")];
+            tensor<int32, [1]> input_5_lstm_layer_0_lstm_h0_squeeze_axes_0 = const()[name = string("input_5_lstm_layer_0_lstm_h0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_5_lstm_layer_0_lstm_h0_squeeze_cast_fp16 = squeeze(axes = input_5_lstm_layer_0_lstm_h0_squeeze_axes_0, x = split_0_cast_fp16_0)[name = string("input_5_lstm_layer_0_lstm_h0_squeeze_cast_fp16")];
+            tensor<int32, [1]> input_5_lstm_layer_0_lstm_c0_squeeze_axes_0 = const()[name = string("input_5_lstm_layer_0_lstm_c0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_5_lstm_layer_0_lstm_c0_squeeze_cast_fp16 = squeeze(axes = input_5_lstm_layer_0_lstm_c0_squeeze_axes_0, x = split_1_cast_fp16_0)[name = string("input_5_lstm_layer_0_lstm_c0_squeeze_cast_fp16")];
+            string input_5_lstm_layer_0_direction_0 = const()[name = string("input_5_lstm_layer_0_direction_0"), val = string("forward")];
+            bool input_5_lstm_layer_0_output_sequence_0 = const()[name = string("input_5_lstm_layer_0_output_sequence_0"), val = bool(true)];
+            string input_5_lstm_layer_0_recurrent_activation_0 = const()[name = string("input_5_lstm_layer_0_recurrent_activation_0"), val = string("sigmoid")];
+            string input_5_lstm_layer_0_cell_activation_0 = const()[name = string("input_5_lstm_layer_0_cell_activation_0"), val = string("tanh")];
+            string input_5_lstm_layer_0_activation_0 = const()[name = string("input_5_lstm_layer_0_activation_0"), val = string("tanh")];
+            tensor<fp16, [2560, 640]> concat_1_to_fp16 = const()[name = string("concat_1_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3621248)))];
+            tensor<fp16, [2560, 640]> concat_2_to_fp16 = const()[name = string("concat_2_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898112)))];
+            tensor<fp16, [2560]> concat_0_to_fp16 = const()[name = string("concat_0_to_fp16"), val = tensor<fp16, [2560]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10174976)))];
+            tensor<fp16, [1, 1, 640]> input_3_cast_fp16 = transpose(perm = input_3_perm_0, x = y_cast_fp16_cast_uint16)[name = string("transpose_4")];
+            tensor<fp16, [1, 1, 640]> input_5_lstm_layer_0_cast_fp16_0, tensor<fp16, [1, 640]> input_5_lstm_layer_0_cast_fp16_1, tensor<fp16, [1, 640]> input_5_lstm_layer_0_cast_fp16_2 = lstm(activation = input_5_lstm_layer_0_activation_0, bias = concat_0_to_fp16, cell_activation = input_5_lstm_layer_0_cell_activation_0, direction = input_5_lstm_layer_0_direction_0, initial_c = input_5_lstm_layer_0_lstm_c0_squeeze_cast_fp16, initial_h = input_5_lstm_layer_0_lstm_h0_squeeze_cast_fp16, output_sequence = input_5_lstm_layer_0_output_sequence_0, recurrent_activation = input_5_lstm_layer_0_recurrent_activation_0, weight_hh = concat_2_to_fp16, weight_ih = concat_1_to_fp16, x = input_3_cast_fp16)[name = string("input_5_lstm_layer_0_cast_fp16")];
+            tensor<int32, [1]> input_5_lstm_h0_squeeze_axes_0 = const()[name = string("input_5_lstm_h0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_5_lstm_h0_squeeze_cast_fp16 = squeeze(axes = input_5_lstm_h0_squeeze_axes_0, x = split_0_cast_fp16_1)[name = string("input_5_lstm_h0_squeeze_cast_fp16")];
+            tensor<int32, [1]> input_5_lstm_c0_squeeze_axes_0 = const()[name = string("input_5_lstm_c0_squeeze_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 640]> input_5_lstm_c0_squeeze_cast_fp16 = squeeze(axes = input_5_lstm_c0_squeeze_axes_0, x = split_1_cast_fp16_1)[name = string("input_5_lstm_c0_squeeze_cast_fp16")];
+            string input_5_direction_0 = const()[name = string("input_5_direction_0"), val = string("forward")];
+            bool input_5_output_sequence_0 = const()[name = string("input_5_output_sequence_0"), val = bool(true)];
+            string input_5_recurrent_activation_0 = const()[name = string("input_5_recurrent_activation_0"), val = string("sigmoid")];
+            string input_5_cell_activation_0 = const()[name = string("input_5_cell_activation_0"), val = string("tanh")];
+            string input_5_activation_0 = const()[name = string("input_5_activation_0"), val = string("tanh")];
+            tensor<fp16, [2560, 640]> concat_4_to_fp16 = const()[name = string("concat_4_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10180160)))];
+            tensor<fp16, [2560, 640]> concat_5_to_fp16 = const()[name = string("concat_5_to_fp16"), val = tensor<fp16, [2560, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13457024)))];
+            tensor<fp16, [2560]> concat_3_to_fp16 = const()[name = string("concat_3_to_fp16"), val = tensor<fp16, [2560]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16733888)))];
+            tensor<fp16, [1, 1, 640]> input_5_cast_fp16_0, tensor<fp16, [1, 640]> input_5_cast_fp16_1, tensor<fp16, [1, 640]> input_5_cast_fp16_2 = lstm(activation = input_5_activation_0, bias = concat_3_to_fp16, cell_activation = input_5_cell_activation_0, direction = input_5_direction_0, initial_c = input_5_lstm_c0_squeeze_cast_fp16, initial_h = input_5_lstm_h0_squeeze_cast_fp16, output_sequence = input_5_output_sequence_0, recurrent_activation = input_5_recurrent_activation_0, weight_hh = concat_5_to_fp16, weight_ih = concat_4_to_fp16, x = input_5_lstm_layer_0_cast_fp16_0)[name = string("input_5_cast_fp16")];
+            int32 obj_3_axis_0 = const()[name = string("obj_3_axis_0"), val = int32(0)];
+            tensor<fp16, [2, 1, 640]> obj_3_cast_fp16 = stack(axis = obj_3_axis_0, values = (input_5_lstm_layer_0_cast_fp16_1, input_5_cast_fp16_1))[name = string("obj_3_cast_fp16")];
+            string obj_3_cast_fp16_to_fp32_dtype_0 = const()[name = string("obj_3_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            int32 obj_axis_0 = const()[name = string("obj_axis_0"), val = int32(0)];
+            tensor<fp16, [2, 1, 640]> obj_cast_fp16 = stack(axis = obj_axis_0, values = (input_5_lstm_layer_0_cast_fp16_2, input_5_cast_fp16_2))[name = string("obj_cast_fp16")];
+            string obj_cast_fp16_to_fp32_dtype_0 = const()[name = string("obj_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
+            tensor<int32, [3]> input_7_perm_0 = const()[name = string("input_7_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
+            string encoder_to_fp16_dtype_0 = const()[name = string("encoder_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [640, 1024]> joint_module_enc_weight_to_fp16 = const()[name = string("joint_module_enc_weight_to_fp16"), val = tensor<fp16, [640, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16739072)))];
+            tensor<fp16, [640]> joint_module_enc_bias_to_fp16 = const()[name = string("joint_module_enc_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18049856)))];
+            tensor<fp16, [1, 1024, 1]> encoder_to_fp16 = cast(dtype = encoder_to_fp16_dtype_0, x = encoder)[name = string("cast_4")];
+            tensor<fp16, [1, 1, 1024]> input_7_cast_fp16 = transpose(perm = input_7_perm_0, x = encoder_to_fp16)[name = string("transpose_2")];
+            tensor<fp16, [1, 1, 640]> linear_0_cast_fp16 = linear(bias = joint_module_enc_bias_to_fp16, weight = joint_module_enc_weight_to_fp16, x = input_7_cast_fp16)[name = string("linear_0_cast_fp16")];
+            tensor<fp16, [640, 640]> joint_module_pred_weight_to_fp16 = const()[name = string("joint_module_pred_weight_to_fp16"), val = tensor<fp16, [640, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18051200)))];
+            tensor<fp16, [640]> joint_module_pred_bias_to_fp16 = const()[name = string("joint_module_pred_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18870464)))];
+            tensor<fp16, [1, 1, 640]> transpose_1_cast_fp16 = transpose(perm = transpose_1_perm_0, x = input_5_cast_fp16_0)[name = string("transpose_3")];
+            tensor<fp16, [1, 1, 640]> linear_1_cast_fp16 = linear(bias = joint_module_pred_bias_to_fp16, weight = joint_module_pred_weight_to_fp16, x = transpose_1_cast_fp16)[name = string("linear_1_cast_fp16")];
+            tensor<int32, [1]> var_79_axes_0 = const()[name = string("op_79_axes_0"), val = tensor<int32, [1]>([2])];
+            tensor<fp16, [1, 1, 1, 640]> var_79_cast_fp16 = expand_dims(axes = var_79_axes_0, x = linear_0_cast_fp16)[name = string("op_79_cast_fp16")];
+            tensor<int32, [1]> var_80_axes_0 = const()[name = string("op_80_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<fp16, [1, 1, 1, 640]> var_80_cast_fp16 = expand_dims(axes = var_80_axes_0, x = linear_1_cast_fp16)[name = string("op_80_cast_fp16")];
+            tensor<fp16, [1, 1, 1, 640]> input_11_cast_fp16 = add(x = var_79_cast_fp16, y = var_80_cast_fp16)[name = string("input_11_cast_fp16")];
+            tensor<fp16, [1, 1, 1, 640]> input_13_cast_fp16 = relu(x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
+            tensor<fp16, [2829, 640]> joint_module_joint_net_2_weight_to_fp16 = const()[name = string("joint_module_joint_net_2_weight_to_fp16"), val = tensor<fp16, [2829, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18871808)))];
+            tensor<fp16, [2829]> joint_module_joint_net_2_bias_to_fp16 = const()[name = string("joint_module_joint_net_2_bias_to_fp16"), val = tensor<fp16, [2829]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22492992)))];
+            tensor<fp16, [1, 1, 1, 2829]> linear_2_cast_fp16 = linear(bias = joint_module_joint_net_2_bias_to_fp16, weight = joint_module_joint_net_2_weight_to_fp16, x = input_13_cast_fp16)[name = string("linear_2_cast_fp16")];
+            string linear_2_cast_fp16_to_fp32_dtype_0 = const()[name = string("linear_2_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            tensor<fp32, [1, 1, 1, 2829]> logits = cast(dtype = linear_2_cast_fp16_to_fp32_dtype_0, x = linear_2_cast_fp16)[name = string("cast_3")];
+            tensor<fp32, [2, 1, 640]> c_out = cast(dtype = obj_cast_fp16_to_fp32_dtype_0, x = obj_cast_fp16)[name = string("cast_5")];
+            tensor<fp32, [2, 1, 640]> h_out = cast(dtype = obj_3_cast_fp16_to_fp32_dtype_0, x = obj_3_cast_fp16)[name = string("cast_6")];
+            tensor<int32, [1]> token_length_tmp = identity(x = token_length)[name = string("token_length_tmp")];
+        } -> (logits, h_out, c_out);
+}

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latin/560ms/joint.mlmodelc/model.mil

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+program(1.3)
+[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})]
+{
+    func main<ios18>(tensor<fp32, [1, 640, 1]> decoder, tensor<fp32, [1, 1024, 1]> encoder) {
+            tensor<int32, [3]> input_1_perm_0 = const()[name = string("input_1_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
+            string encoder_to_fp16_dtype_0 = const()[name = string("encoder_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<int32, [3]> input_3_perm_0 = const()[name = string("input_3_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
+            string decoder_to_fp16_dtype_0 = const()[name = string("decoder_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [640, 1024]> module_enc_weight_to_fp16 = const()[name = string("module_enc_weight_to_fp16"), val = tensor<fp16, [640, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
+            tensor<fp16, [640]> module_enc_bias_to_fp16 = const()[name = string("module_enc_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1310848)))];
+            tensor<fp16, [1, 1024, 1]> encoder_to_fp16 = cast(dtype = encoder_to_fp16_dtype_0, x = encoder)[name = string("cast_2")];
+            tensor<fp16, [1, 1, 1024]> input_1_cast_fp16 = transpose(perm = input_1_perm_0, x = encoder_to_fp16)[name = string("transpose_1")];
+            tensor<fp16, [1, 1, 640]> linear_0_cast_fp16 = linear(bias = module_enc_bias_to_fp16, weight = module_enc_weight_to_fp16, x = input_1_cast_fp16)[name = string("linear_0_cast_fp16")];
+            tensor<fp16, [640, 640]> module_pred_weight_to_fp16 = const()[name = string("module_pred_weight_to_fp16"), val = tensor<fp16, [640, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1312192)))];
+            tensor<fp16, [640]> module_pred_bias_to_fp16 = const()[name = string("module_pred_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2131456)))];
+            tensor<fp16, [1, 640, 1]> decoder_to_fp16 = cast(dtype = decoder_to_fp16_dtype_0, x = decoder)[name = string("cast_1")];
+            tensor<fp16, [1, 1, 640]> input_3_cast_fp16 = transpose(perm = input_3_perm_0, x = decoder_to_fp16)[name = string("transpose_0")];
+            tensor<fp16, [1, 1, 640]> linear_1_cast_fp16 = linear(bias = module_pred_bias_to_fp16, weight = module_pred_weight_to_fp16, x = input_3_cast_fp16)[name = string("linear_1_cast_fp16")];
+            tensor<int32, [1]> var_23_axes_0 = const()[name = string("op_23_axes_0"), val = tensor<int32, [1]>([2])];
+            tensor<fp16, [1, 1, 1, 640]> var_23_cast_fp16 = expand_dims(axes = var_23_axes_0, x = linear_0_cast_fp16)[name = string("op_23_cast_fp16")];
+            tensor<int32, [1]> var_25_axes_0 = const()[name = string("op_25_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<fp16, [1, 1, 1, 640]> var_25_cast_fp16 = expand_dims(axes = var_25_axes_0, x = linear_1_cast_fp16)[name = string("op_25_cast_fp16")];
+            tensor<fp16, [1, 1, 1, 640]> input_5_cast_fp16 = add(x = var_23_cast_fp16, y = var_25_cast_fp16)[name = string("input_5_cast_fp16")];
+            tensor<fp16, [1, 1, 1, 640]> input_7_cast_fp16 = relu(x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
+            tensor<fp16, [2829, 640]> module_joint_net_2_weight_to_fp16 = const()[name = string("module_joint_net_2_weight_to_fp16"), val = tensor<fp16, [2829, 640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2132800)))];
+            tensor<fp16, [2829]> module_joint_net_2_bias_to_fp16 = const()[name = string("module_joint_net_2_bias_to_fp16"), val = tensor<fp16, [2829]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5753984)))];
+            tensor<fp16, [1, 1, 1, 2829]> linear_2_cast_fp16 = linear(bias = module_joint_net_2_bias_to_fp16, weight = module_joint_net_2_weight_to_fp16, x = input_7_cast_fp16)[name = string("linear_2_cast_fp16")];
+            string linear_2_cast_fp16_to_fp32_dtype_0 = const()[name = string("linear_2_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            tensor<fp32, [1, 1, 1, 2829]> logits = cast(dtype = linear_2_cast_fp16_to_fp32_dtype_0, x = linear_2_cast_fp16)[name = string("cast_0")];
+        } -> (logits);
+}

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latin/560ms/metadata.json

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+{
+  "model": "nvidia/nemotron-asr-streaming-multilingual-0.6b",
+  "model_class": "nemo.collections.asr.models.rnnt_bpe_models_prompt.EncDecRNNTBPEModelWithPrompt",
+  "sample_rate": 16000,
+  "mel_features": 128,
+  "chunk_mel_frames": 56,
+  "pre_encode_cache": 9,
+  "total_mel_frames": 65,
+  "att_context_size": [
+    42,
+    13
+  ],
+  "vocab_size": 2828,
+  "blank_idx": 2828,
+  "vocab_pruned": true,
+  "vocab_pruned_original_size": 13087,
+  "cache_channel_shape": [
+    1,
+    24,
+    42,
+    1024
+  ],
+  "cache_time_shape": [
+    1,
+    24,
+    1024,
+    8
+  ],
+  "decoder_hidden": 640,
+  "decoder_layers": 2,
+  "encoder_dim": 1024,
+  "num_prompts": 128,
+  "prompt_dictionary": {
+    "en-US": 0,
+    "en": 0,
+    "en-GB": 1,
+    "enGB": 1,
+    "es-ES": 2,
+    "esES": 2,
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+    "zh-CN": 4,
+    "zh-ZH": 4,
+    "zh-TW": 5,
+    "hi-IN": 6,
+    "hi": 6,
+    "hi-HI": 6,
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+    "ar": 7,
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+    "fr": 8,
+    "de-DE": 9,
+    "de": 9,
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+    "ru": 11,
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+    "pt": 13,
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+    "ko-KO": 14,
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+    "it": 15,
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+    "no-NO": 27,
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+    "nb-NO": 103,
+    "nb": 103,
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+    "nn": 104,
+    "sk-SK": 28,
+    "sk": 28,
+    "hr-HR": 29,
+    "hr": 29,
+    "bg-BG": 30,
+    "bg": 30,
+    "lt-LT": 31,
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+    "et-EE": 60,
+    "et": 60,
+    "lv-LV": 61,
+    "lv": 61,
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+    "te-IN": 40,
+    "mr-IN": 41,
+    "gu-IN": 42,
+    "kn-IN": 43,
+    "ml-IN": 44,
+    "si-LK": 45,
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+    "sm-WS": 98,
+    "to-TO": 99,
+    "fr-CA": 100,
+    "mt-MT": 102,
+    "auto": 101
+  },
+  "default_prompt_id": 101,
+  "lang_tag_token_ids": [
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+    358,
+    513,
+    654,
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+    2685
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+}

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latin/560ms/preprocessor.mlmodelc/model.mil

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+program(1.3)
+[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})]
+{
+    func main<ios18>(tensor<fp32, [1, ?]> audio, tensor<int32, [1]> audio_length) [FlexibleShapeInformation = tuple<tuple<string, dict<string, tensor<int32, [?]>>>, tuple<string, dict<string, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"audio", [1, 1]}}), ("RangeDims", {{"audio", [[1, 1], [1, 1280000]]}})))] {
+            int32 var_9 = const()[name = string("op_9"), val = int32(1)];
+            int32 var_10 = const()[name = string("op_10"), val = int32(160)];
+            int32 var_12 = const()[name = string("op_12"), val = int32(0)];
+            int32 var_33 = const()[name = string("op_33"), val = int32(512)];
+            tensor<int32, [1]> var_34 = add(x = audio_length, y = var_33)[name = string("op_34")];
+            int32 var_35 = const()[name = string("op_35"), val = int32(512)];
+            tensor<int32, [1]> var_36 = sub(x = var_34, y = var_35)[name = string("op_36")];
+            tensor<int32, [1]> floor_div_0 = floor_div(x = var_36, y = var_10)[name = string("floor_div_0")];
+            tensor<bool, [1]> var_39 = equal(x = audio_length, y = var_12)[name = string("op_39")];
+            tensor<int32, [1]> var_40 = const()[name = string("op_40"), val = tensor<int32, [1]>([0])];
+            tensor<int32, [1]> mel_length = select(a = var_40, b = floor_div_0, cond = var_39)[name = string("seq_len")];
+            string audio_to_fp16_dtype_0 = const()[name = string("audio_to_fp16_dtype_0"), val = string("fp16")];
+            tensor<fp16, [1, ?]> audio_to_fp16 = cast(dtype = audio_to_fp16_dtype_0, x = audio)[name = string("cast_14")];
+            tensor<int32, [2]> var_42_shape_cast_fp16 = shape(x = audio_to_fp16)[name = string("op_42_shape_cast_fp16")];
+            int32 gather_0_axis_0 = const()[name = string("gather_0_axis_0"), val = int32(0)];
+            int32 gather_0_batch_dims_0 = const()[name = string("gather_0_batch_dims_0"), val = int32(0)];
+            bool gather_0_validate_indices_0 = const()[name = string("gather_0_validate_indices_0"), val = bool(false)];
+            string var_42_shape_cast_fp16_to_int16_dtype_0 = const()[name = string("op_42_shape_cast_fp16_to_int16_dtype_0"), val = string("int16")];
+            uint16 select_0_to_uint16 = const()[name = string("select_0_to_uint16"), val = uint16(1)];
+            tensor<int16, [2]> var_42_shape_cast_fp16_to_int16 = cast(dtype = var_42_shape_cast_fp16_to_int16_dtype_0, x = var_42_shape_cast_fp16)[name = string("cast_13")];
+            int16 gather_0_cast_uint16 = gather(axis = gather_0_axis_0, batch_dims = gather_0_batch_dims_0, indices = select_0_to_uint16, validate_indices = gather_0_validate_indices_0, x = var_42_shape_cast_fp16_to_int16)[name = string("gather_0_cast_uint16")];
+            string gather_0_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_0_cast_uint16_to_int32_dtype_0"), val = string("int32")];
+            int32 const_0 = const()[name = string("const_0"), val = int32(0)];
+            int32 const_1 = const()[name = string("const_1"), val = int32(1)];
+            int32 gather_0_cast_uint16_to_int32 = cast(dtype = gather_0_cast_uint16_to_int32_dtype_0, x = gather_0_cast_uint16)[name = string("cast_12")];
+            tensor<int32, [?]> var_43 = range_1d(end = gather_0_cast_uint16_to_int32, start = const_0, step = const_1)[name = string("op_43")];
+            tensor<int32, [1]> var_44_axes_0 = const()[name = string("op_44_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<int32, [1, ?]> var_44 = expand_dims(axes = var_44_axes_0, x = var_43)[name = string("op_44")];
+            tensor<int32, [1]> var_45_axes_0 = const()[name = string("op_45_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<int32, [1, 1]> var_45 = expand_dims(axes = var_45_axes_0, x = audio_length)[name = string("op_45")];
+            tensor<bool, [1, ?]> timemask = less(x = var_44, y = var_45)[name = string("timemask")];
+            tensor<int32, [2]> var_48_begin_0 = const()[name = string("op_48_begin_0"), val = tensor<int32, [2]>([0, 0])];
+            tensor<int32, [2]> var_48_end_0 = const()[name = string("op_48_end_0"), val = tensor<int32, [2]>([1, 1])];
+            tensor<bool, [2]> var_48_end_mask_0 = const()[name = string("op_48_end_mask_0"), val = tensor<bool, [2]>([true, false])];
+            tensor<bool, [2]> var_48_squeeze_mask_0 = const()[name = string("op_48_squeeze_mask_0"), val = tensor<bool, [2]>([false, true])];
+            tensor<fp16, [1]> var_48_cast_fp16 = slice_by_index(begin = var_48_begin_0, end = var_48_end_0, end_mask = var_48_end_mask_0, squeeze_mask = var_48_squeeze_mask_0, x = audio_to_fp16)[name = string("op_48_cast_fp16")];
+            tensor<int32, [1]> var_49_axes_0 = const()[name = string("op_49_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<fp16, [1, 1]> var_49_cast_fp16 = expand_dims(axes = var_49_axes_0, x = var_48_cast_fp16)[name = string("op_49_cast_fp16")];
+            tensor<int32, [2]> var_51_begin_0 = const()[name = string("op_51_begin_0"), val = tensor<int32, [2]>([0, 1])];
+            tensor<int32, [2]> var_51_end_0 = const()[name = string("op_51_end_0"), val = tensor<int32, [2]>([1, 0])];
+            tensor<bool, [2]> var_51_end_mask_0 = const()[name = string("op_51_end_mask_0"), val = tensor<bool, [2]>([true, true])];
+            tensor<fp16, [1, ?]> var_51_cast_fp16 = slice_by_index(begin = var_51_begin_0, end = var_51_end_0, end_mask = var_51_end_mask_0, x = audio_to_fp16)[name = string("op_51_cast_fp16")];
+            tensor<int32, [2]> var_53_begin_0 = const()[name = string("op_53_begin_0"), val = tensor<int32, [2]>([0, 0])];
+            tensor<int32, [2]> var_53_end_0 = const()[name = string("op_53_end_0"), val = tensor<int32, [2]>([1, -1])];
+            tensor<bool, [2]> var_53_end_mask_0 = const()[name = string("op_53_end_mask_0"), val = tensor<bool, [2]>([true, false])];
+            tensor<fp16, [1, ?]> var_53_cast_fp16 = slice_by_index(begin = var_53_begin_0, end = var_53_end_0, end_mask = var_53_end_mask_0, x = audio_to_fp16)[name = string("op_53_cast_fp16")];
+            fp16 var_54_to_fp16 = const()[name = string("op_54_to_fp16"), val = fp16(0x1.f0cp-1)];
+            tensor<fp16, [1, ?]> var_55_cast_fp16 = mul(x = var_53_cast_fp16, y = var_54_to_fp16)[name = string("op_55_cast_fp16")];
+            tensor<fp16, [1, ?]> var_56_cast_fp16 = sub(x = var_51_cast_fp16, y = var_55_cast_fp16)[name = string("op_56_cast_fp16")];
+            bool x_3_interleave_0 = const()[name = string("x_3_interleave_0"), val = bool(false)];
+            tensor<fp16, [1, ?]> x_3_cast_fp16 = concat(axis = var_9, interleave = x_3_interleave_0, values = (var_49_cast_fp16, var_56_cast_fp16))[name = string("x_3_cast_fp16")];
+            tensor<bool, [1, ?]> var_59 = logical_not(x = timemask)[name = string("op_59")];
+            fp16 var_16_to_fp16 = const()[name = string("op_16_to_fp16"), val = fp16(0x0p+0)];
+            tensor<fp16, [1, ?]> input_1_cast_fp16 = select(a = var_16_to_fp16, b = x_3_cast_fp16, cond = var_59)[name = string("input_1_cast_fp16")];
+            tensor<int32, [3]> concat_1x = const()[name = string("concat_1x"), val = tensor<int32, [3]>([1, 1, -1])];
+            tensor<fp16, [1, 1, ?]> input_3_cast_fp16 = reshape(shape = concat_1x, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
+            tensor<int32, [6]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 256, 256])];
+            string input_5_mode_0 = const()[name = string("input_5_mode_0"), val = string("constant")];
+            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
+            tensor<fp16, [1, 1, ?]> input_5_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_5_mode_0, pad = input_5_pad_0, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
+            tensor<int32, [2]> concat_2x = const()[name = string("concat_2x"), val = tensor<int32, [2]>([1, -1])];
+            tensor<fp16, [1, ?]> input_cast_fp16 = reshape(shape = concat_2x, x = input_5_cast_fp16)[name = string("input_cast_fp16")];
+            tensor<int32, [1]> expand_dims_3 = const()[name = string("expand_dims_3"), val = tensor<int32, [1]>([160])];
+            tensor<int32, [1]> expand_dims_4_axes_0 = const()[name = string("expand_dims_4_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<fp16, [1, 1, ?]> expand_dims_4_cast_fp16 = expand_dims(axes = expand_dims_4_axes_0, x = input_cast_fp16)[name = string("expand_dims_4_cast_fp16")];
+            string conv_0_pad_type_0 = const()[name = string("conv_0_pad_type_0"), val = string("valid")];
+            tensor<int32, [2]> conv_0_pad_0 = const()[name = string("conv_0_pad_0"), val = tensor<int32, [2]>([0, 0])];
+            tensor<int32, [1]> conv_0_dilations_0 = const()[name = string("conv_0_dilations_0"), val = tensor<int32, [1]>([1])];
+            int32 conv_0_groups_0 = const()[name = string("conv_0_groups_0"), val = int32(1)];
+            tensor<fp16, [257, 1, 512]> expand_dims_1_to_fp16 = const()[name = string("expand_dims_1_to_fp16"), val = tensor<fp16, [257, 1, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
+            tensor<fp16, [1, 257, ?]> conv_0_cast_fp16 = conv(dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = expand_dims_3, weight = expand_dims_1_to_fp16, x = expand_dims_4_cast_fp16)[name = string("conv_0_cast_fp16")];
+            string conv_1_pad_type_0 = const()[name = string("conv_1_pad_type_0"), val = string("valid")];
+            tensor<int32, [2]> conv_1_pad_0 = const()[name = string("conv_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
+            tensor<int32, [1]> conv_1_dilations_0 = const()[name = string("conv_1_dilations_0"), val = tensor<int32, [1]>([1])];
+            int32 conv_1_groups_0 = const()[name = string("conv_1_groups_0"), val = int32(1)];
+            tensor<fp16, [257, 1, 512]> expand_dims_2_to_fp16 = const()[name = string("expand_dims_2_to_fp16"), val = tensor<fp16, [257, 1, 512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(263296)))];
+            tensor<fp16, [1, 257, ?]> conv_1_cast_fp16 = conv(dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = expand_dims_3, weight = expand_dims_2_to_fp16, x = expand_dims_4_cast_fp16)[name = string("conv_1_cast_fp16")];
+            int32 stack_0_axis_0 = const()[name = string("stack_0_axis_0"), val = int32(-1)];
+            tensor<fp16, [1, 257, ?, 2]> stack_0_cast_fp16 = stack(axis = stack_0_axis_0, values = (conv_0_cast_fp16, conv_1_cast_fp16))[name = string("stack_0_cast_fp16")];
+            fp16 var_19_promoted_to_fp16 = const()[name = string("op_19_promoted_to_fp16"), val = fp16(0x1p+1)];
+            tensor<fp16, [1, 257, ?, 2]> var_74_cast_fp16 = pow(x = stack_0_cast_fp16, y = var_19_promoted_to_fp16)[name = string("op_74_cast_fp16")];
+            tensor<int32, [1]> var_76_axes_0 = const()[name = string("op_76_axes_0"), val = tensor<int32, [1]>([-1])];
+            bool var_76_keep_dims_0 = const()[name = string("op_76_keep_dims_0"), val = bool(false)];
+            tensor<fp16, [1, 257, ?]> var_76_cast_fp16 = reduce_sum(axes = var_76_axes_0, keep_dims = var_76_keep_dims_0, x = var_74_cast_fp16)[name = string("op_76_cast_fp16")];
+            tensor<fp16, [1, 257, ?]> x_11_cast_fp16 = identity(x = var_76_cast_fp16)[name = string("x_11_cast_fp16")];
+            bool x_13_transpose_x_0 = const()[name = string("x_13_transpose_x_0"), val = bool(false)];
+            bool x_13_transpose_y_0 = const()[name = string("x_13_transpose_y_0"), val = bool(false)];
+            tensor<fp16, [1, 128, 257]> const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = tensor<fp16, [1, 128, 257]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(526528)))];
+            tensor<fp16, [1, 128, ?]> x_13_cast_fp16 = matmul(transpose_x = x_13_transpose_x_0, transpose_y = x_13_transpose_y_0, x = const_4_to_fp16, y = x_11_cast_fp16)[name = string("x_13_cast_fp16")];
+            fp16 var_83_to_fp16 = const()[name = string("op_83_to_fp16"), val = fp16(0x1p-24)];
+            tensor<fp16, [1, 128, ?]> var_84_cast_fp16 = add(x = x_13_cast_fp16, y = var_83_to_fp16)[name = string("op_84_cast_fp16")];
+            fp32 x_epsilon_0 = const()[name = string("x_epsilon_0"), val = fp32(0x1p-149)];
+            tensor<fp16, [1, 128, ?]> x_cast_fp16 = log(epsilon = x_epsilon_0, x = var_84_cast_fp16)[name = string("x_cast_fp16")];
+            tensor<int32, [3]> var_86_shape_cast_fp16 = shape(x = x_cast_fp16)[name = string("op_86_shape_cast_fp16")];
+            int32 gather_5_axis_0 = const()[name = string("gather_5_axis_0"), val = int32(0)];
+            int32 gather_5_batch_dims_0 = const()[name = string("gather_5_batch_dims_0"), val = int32(0)];
+            bool gather_5_validate_indices_0 = const()[name = string("gather_5_validate_indices_0"), val = bool(false)];
+            string var_86_shape_cast_fp16_to_uint16_dtype_0 = const()[name = string("op_86_shape_cast_fp16_to_uint16_dtype_0"), val = string("uint16")];
+            uint16 select_5_to_uint16 = const()[name = string("select_5_to_uint16"), val = uint16(2)];
+            tensor<uint16, [3]> var_86_shape_cast_fp16_to_uint16 = cast(dtype = var_86_shape_cast_fp16_to_uint16_dtype_0, x = var_86_shape_cast_fp16)[name = string("cast_11")];
+            uint16 gather_5_cast_uint16 = gather(axis = gather_5_axis_0, batch_dims = gather_5_batch_dims_0, indices = select_5_to_uint16, validate_indices = gather_5_validate_indices_0, x = var_86_shape_cast_fp16_to_uint16)[name = string("gather_5_cast_uint16")];
+            string gather_5_cast_uint16_to_int32_dtype_0 = const()[name = string("gather_5_cast_uint16_to_int32_dtype_0"), val = string("int32")];
+            int32 const_5 = const()[name = string("const_5"), val = int32(0)];
+            int32 const_6 = const()[name = string("const_6"), val = int32(1)];
+            int32 gather_5_cast_uint16_to_int32 = cast(dtype = gather_5_cast_uint16_to_int32_dtype_0, x = gather_5_cast_uint16)[name = string("cast_10")];
+            tensor<int32, [?]> mask_1 = range_1d(end = gather_5_cast_uint16_to_int32, start = const_5, step = const_6)[name = string("mask_1")];
+            tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = string("expand_dims_0_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<int32, [1, ?]> expand_dims_0 = expand_dims(axes = expand_dims_0_axes_0, x = mask_1)[name = string("expand_dims_0")];
+            tensor<int32, [1]> var_91_axes_0 = const()[name = string("op_91_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<int32, [1, 1]> var_91 = expand_dims(axes = var_91_axes_0, x = mel_length)[name = string("op_91")];
+            tensor<bool, [1, ?]> mask = greater_equal(x = expand_dims_0, y = var_91)[name = string("mask")];
+            tensor<int32, [1]> var_93_axes_0 = const()[name = string("op_93_axes_0"), val = tensor<int32, [1]>([1])];
+            tensor<bool, [1, 1, ?]> var_93 = expand_dims(axes = var_93_axes_0, x = mask)[name = string("op_93")];
+            tensor<fp16, [1, 128, ?]> processed_signal_cast_fp16 = select(a = var_16_to_fp16, b = x_cast_fp16, cond = var_93)[name = string("processed_signal_cast_fp16")];
+            string processed_signal_cast_fp16_to_fp32_dtype_0 = const()[name = string("processed_signal_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
+            tensor<fp32, [1, 128, ?]> mel = cast(dtype = processed_signal_cast_fp16_to_fp32_dtype_0, x = processed_signal_cast_fp16)[name = string("cast_9")];
+        } -> (mel, mel_length);
+}

latin/560ms/preprocessor.mlmodelc/weights/weight.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:297514e2b211d14b0e53cb97193d679bb89ead98d28e578f3f1d049ddbcc36b3
+size 592384

latin/560ms/tokenizer.json

@@ -0,0 +1,2831 @@
+{
+  "0": "<unk>",
+  "1": "<bg-BG>",
+  "2": "▁",
+  "3": ".",
+  "4": ",",
+  "5": "e",
+  "6": "t",
+  "7": "a",
+  "8": "s",
+  "9": "o",
+  "10": "i",
+  "11": "r",
+  "12": "l",
+  "13": "u",
+  "14": "d",
+  "15": "c",
+  "16": "h",
+  "17": "m",
+  "18": "p",
+  "19": "n",
+  "20": "g",
+  "21": "f",
+  "22": "en",
+  "23": "in",
+  "24": "on",
+  "25": "y",
+  "26": "er",
+  "27": "an",
+  "28": "w",
+  "29": "0",
+  "30": "b",
+  "31": "v",
+  "32": "2",
+  "33": "1",
+  "34": "▁the",
+  "35": "k",
+  "36": "?",
+  "37": "3",
+  "38": "5",
+  "39": "q",
+  "40": "I",
+  "41": "é",
+  "42": "4",
+  "43": "z",
+  "44": "A",
+  "45": "6",
+  "46": "j",
+  "47": "E",
+  "48": "7",
+  "49": "T",
+  "50": "8",
+  "51": "9",
+  "52": "S",
+  "53": "x",
+  "54": "C",
+  "55": "M",
+  "56": "P",
+  "57": "D",
+  "58": "B",
+  "59": "U",
+  "60": "W",
+  "61": "N",
+  "62": "O",
+  "63": "G",
+  "64": "à",
+  "65": "F",
+  "66": "L",
+  "67": "è",
+  "68": "V",
+  "69": "R",
+  "70": "ó",
+  "71": "H",
+  "72": "α",
+  "73": "ü",
+  "74": "ä",
+  "75": "J",
+  "76": "í",
+  "77": "τ",
+  "78": "ι",
+  "79": "á",
+  "80": "ο",
+  "81": "K",
+  "82": "ε",
+  "83": "ê",
+  "84": "Y",
+  "85": "ν",
+  "86": "ö",
+  "87": "ç",
+  "88": "ρ",
+  "89": "σ",
+  "90": "π",
+  "91": "ę",
+  "92": "υ",
+  "93": "η",
+  "94": "μ",
+  "95": "κ",
+  "96": "<cs-CZ>",
+  "97": "st",
+  "98": "ch",
+  "99": "ní",
+  "100": "▁s",
+  "101": "le",
+  "102": "li",
+  "103": "▁po",
+  "104": "▁v",
+  "105": "ž",
+  "106": "č",
+  "107": "▁to",
+  "108": "no",
+  "109": "to",
+  "110": "▁z",
+  "111": "me",
+  "112": "▁se",
+  "113": "▁a",
+  "114": "te",
+  "115": "▁je",
+  "116": "ho",
+  "117": "▁pro",
+  "118": "ů",
+  "119": "ně",
+  "120": "ro",
+  "121": "▁na",
+  "122": "ce",
+  "123": "▁o",
+  "124": "la",
+  "125": "š",
+  "126": "▁ne",
+  "127": "ni",
+  "128": "ra",
+  "129": "ti",
+  "130": "lo",
+  "131": "ko",
+  "132": "▁že",
+  "133": "ná",
+  "134": "po",
+  "135": "je",
+  "136": "ě",
+  "137": "de",
+  "138": "na",
+  "139": "mi",
+  "140": "▁do",
+  "141": "ci",
+  "142": "▁k",
+  "143": "ku",
+  "144": "ře",
+  "145": "▁by",
+  "146": "ve",
+  "147": "▁za",
+  "148": "mě",
+  "149": "▁A",
+  "150": "ý",
+  "151": "re",
+  "152": "vá",
+  "153": "ou",
+  "154": "vo",
+  "155": "né",
+  "156": "va",
+  "157": "že",
+  "158": "mo",
+  "159": "vě",
+  "160": "jí",
+  "161": "tě",
+  "162": "vý",
+  "163": "▁tak",
+  "164": "ze",
+  "165": "ří",
+  "166": "ne",
+  "167": "še",
+  "168": "▁vy",
+  "169": "ka",
+  "170": "ji",
+  "171": "ky",
+  "172": "rá",
+  "173": "ovat",
+  "174": "▁ob",
+  "175": "cí",
+  "176": "▁jak",
+  "177": "▁pře",
+  "178": "ny",
+  "179": "ví",
+  "180": "ný",
+  "181": "vi",
+  "182": "▁in",
+  "183": "práv",
+  "184": "ú",
+  "185": "▁co",
+  "186": "▁také",
+  "187": "ent",
+  "188": "▁pan",
+  "189": "▁Děkuji",
+  "190": "▁které",
+  "191": "ři",
+  "192": "▁aby",
+  "193": "▁pří",
+  "194": "▁při",
+  "195": "prav",
+  "196": "ř",
+  "197": "vrop",
+  "198": "▁bude",
+  "199": "▁roz",
+  "200": "▁jsou",
+  "201": "ové",
+  "202": "▁jsme",
+  "203": "ské",
+  "204": "ování",
+  "205": "▁tady",
+  "206": "ský",
+  "207": "děl",
+  "208": "▁musí",
+  "209": "Z",
+  "210": "klad",
+  "211": "▁tedy",
+  "212": "dob",
+  "213": "▁To",
+  "214": "ální",
+  "215": "▁Je",
+  "216": "▁stát",
+  "217": "ň",
+  "218": "oval",
+  "219": "▁protože",
+  "220": "▁jsem",
+  "221": "▁který",
+  "222": "předsed",
+  "223": "▁být",
+  "224": "ď",
+  "225": "Č",
+  "226": "ť",
+  "227": "Š",
+  "228": "Ř",
+  "229": "Ž",
+  "230": "ă",
+  "231": "ł",
+  "232": "ż",
+  "233": "ą",
+  "234": "X",
+  "235": "Ú",
+  "236": "ś",
+  "237": "<da-DK>",
+  "238": "▁for",
+  "239": "▁det",
+  "240": "▁at",
+  "241": "æ",
+  "242": "et",
+  "243": "▁og",
+  "244": "▁vi",
+  "245": "al",
+  "246": "▁de",
+  "247": "▁der",
+  "248": "▁til",
+  "249": "or",
+  "250": "▁er",
+  "251": "om",
+  "252": "å",
+  "253": "ø",
+  "254": "and",
+  "255": "▁har",
+  "256": "at",
+  "257": "▁f",
+  "258": "▁i",
+  "259": "▁så",
+  "260": "▁af",
+  "261": "ge",
+  "262": "ar",
+  "263": "is",
+  "264": "ing",
+  "265": "▁med",
+  "266": "▁på",
+  "267": "▁be",
+  "268": "un",
+  "269": "lig",
+  "270": "▁ikke",
+  "271": "▁man",
+  "272": "ig",
+  "273": "▁som",
+  "274": "ør",
+  "275": "▁Og",
+  "276": "el",
+  "277": "ag",
+  "278": "▁skal",
+  "279": "erne",
+  "280": "▁Det",
+  "281": "▁den",
+  "282": "ste",
+  "283": "ning",
+  "284": "▁jeg",
+  "285": "id",
+  "286": "▁kan",
+  "287": "▁også",
+  "288": "▁vil",
+  "289": "ske",
+  "290": "iv",
+  "291": "▁ud",
+  "292": "▁her",
+  "293": "ion",
+  "294": "am",
+  "295": "ur",
+  "296": "for",
+  "297": "▁pr",
+  "298": "else",
+  "299": "▁sig",
+  "300": "▁men",
+  "301": "▁ind",
+  "302": "▁jo",
+  "303": "ende",
+  "304": "▁være",
+  "305": "▁Vi",
+  "306": "ation",
+  "307": "▁må",
+  "308": "mme",
+  "309": "ighed",
+  "310": "tage",
+  "311": "▁op",
+  "312": "▁Jeg",
+  "313": "▁hvor",
+  "314": "▁ved",
+  "315": "▁få",
+  "316": "▁fra",
+  "317": "▁over",
+  "318": "▁have",
+  "319": "kke",
+  "320": "▁meget",
+  "321": "▁Så",
+  "322": "▁Tak",
+  "323": "▁noget",
+  "324": "▁alle",
+  "325": "brug",
+  "326": "▁komme",
+  "327": "▁Men",
+  "328": "▁var",
+  "329": "hold",
+  "330": "arbejde",
+  "331": "▁eller",
+  "332": "▁vores",
+  "333": "▁frem",
+  "334": "▁altså",
+  "335": "▁vigtig",
+  "336": "vær",
+  "337": "▁EU",
+  "338": "▁gøre",
+  "339": "▁nogle",
+  "340": "skab",
+  "341": "▁spørgsmål",
+  "342": "▁kunne",
+  "343": "▁kommissionen",
+  "344": "▁hvis",
+  "345": "Ø",
+  "346": "Æ",
+  "347": "ς",
+  "348": "λ",
+  "349": "ί",
+  "350": "ό",
+  "351": "ı",
+  "352": "έ",
+  "353": "ά",
+  "354": "ω",
+  "355": "γ",
+  "356": "δ",
+  "357": "ή",
+  "358": "<de-DE>",
+  "359": "▁die",
+  "360": "▁und",
+  "361": "▁das",
+  "362": "sch",
+  "363": "▁ist",
+  "364": "▁ich",
+  "365": "▁ein",
+  "366": "▁ge",
+  "367": "ung",
+  "368": "it",
+  "369": "▁wir",
+  "370": "▁zu",
+  "371": "▁so",
+  "372": "▁da",
+  "373": "▁S",
+  "374": "▁auch",
+  "375": "gen",
+  "376": "▁nicht",
+  "377": "▁W",
+  "378": "▁B",
+  "379": "▁E",
+  "380": "▁F",
+  "381": "ll",
+  "382": "▁es",
+  "383": "▁K",
+  "384": "ie",
+  "385": "au",
+  "386": "▁P",
+  "387": "ich",
+  "388": "▁eine",
+  "389": "lich",
+  "390": "ck",
+  "391": "ten",
+  "392": "mal",
+  "393": "ein",
+  "394": "▁T",
+  "395": "▁dann",
+  "396": "▁Und",
+  "397": "▁mit",
+  "398": "▁auf",
+  "399": "hr",
+  "400": "ter",
+  "401": "tz",
+  "402": "▁dass",
+  "403": "▁G",
+  "404": "ben",
+  "405": "um",
+  "406": "us",
+  "407": "cht",
+  "408": "il",
+  "409": "▁Das",
+  "410": "▁diese",
+  "411": "▁noch",
+  "412": "▁jetzt",
+  "413": "ut",
+  "414": "▁ver",
+  "415": "kt",
+  "416": "▁Ich",
+  "417": "▁hier",
+  "418": "▁hat",
+  "419": "▁haben",
+  "420": "▁von",
+  "421": "ri",
+  "422": "ach",
+  "423": "ol",
+  "424": "▁Da",
+  "425": "▁als",
+  "426": "sp",
+  "427": "▁für",
+  "428": "ell",
+  "429": "▁sich",
+  "430": "▁was",
+  "431": "▁ja",
+  "432": "uch",
+  "433": "▁kann",
+  "434": "▁sind",
+  "435": "wi",
+  "436": "▁aus",
+  "437": "rei",
+  "438": "▁wie",
+  "439": "▁Ge",
+  "440": "und",
+  "441": "▁St",
+  "442": "isch",
+  "443": "▁sie",
+  "444": "▁Ja",
+  "445": "▁du",
+  "446": "▁war",
+  "447": "▁im",
+  "448": "▁dem",
+  "449": "▁aber",
+  "450": "▁oder",
+  "451": "ß",
+  "452": "▁Sch",
+  "453": "▁uns",
+  "454": "▁habe",
+  "455": "▁wenn",
+  "456": "▁wo",
+  "457": "▁bei",
+  "458": "▁ihr",
+  "459": "▁Ma",
+  "460": "zu",
+  "461": "▁schon",
+  "462": "▁De",
+  "463": "▁Sie",
+  "464": "▁über",
+  "465": "▁vor",
+  "466": "▁Die",
+  "467": "▁ganz",
+  "468": "iert",
+  "469": "▁Le",
+  "470": "▁viel",
+  "471": "▁In",
+  "472": "▁Also",
+  "473": "▁Ver",
+  "474": "▁sehr",
+  "475": "▁Re",
+  "476": "halt",
+  "477": "▁einfach",
+  "478": "▁werden",
+  "479": "▁sein",
+  "480": "▁Wir",
+  "481": "▁nur",
+  "482": "▁immer",
+  "483": "ieren",
+  "484": "▁muss",
+  "485": "▁wieder",
+  "486": "▁mir",
+  "487": "▁gut",
+  "488": "▁mehr",
+  "489": "▁Mi",
+  "490": "▁nach",
+  "491": "▁Ha",
+  "492": "▁weil",
+  "493": "▁Aber",
+  "494": "kommen",
+  "495": "▁gibt",
+  "496": "▁meine",
+  "497": "▁andere",
+  "498": "▁können",
+  "499": "▁machen",
+  "500": "▁natürlich",
+  "501": "▁bisschen",
+  "502": "▁durch",
+  "503": "sehen",
+  "504": "▁weiter",
+  "505": "▁keine",
+  "506": "▁sagen",
+  "507": "▁wirklich",
+  "508": "▁eigentlich",
+  "509": "▁jede",
+  "510": "schaft",
+  "511": "▁glaube",
+  "512": "Ü",
+  "513": "<el-GR>",
+  "514": "χ",
+  "515": "τα",
+  "516": "▁να",
+  "517": "ει",
+  "518": "▁και",
+  "519": "μα",
+  "520": "β",
+  "521": "ση",
+  "522": "τε",
+  "523": "ώ",
+  "524": "θ",
+  "525": "φ",
+  "526": "πο",
+  "527": "ύ",
+  "528": "▁το",
+  "529": "ία",
+  "530": "τι",
+  "531": "αν",
+  "532": "ου",
+  "533": "ρα",
+  "534": "▁για",
+  "535": "εί",
+  "536": "τη",
+  "537": "ξ",
+  "538": "κα",
+  "539": "▁την",
+  "540": "▁τη",
+  "541": "με",
+  "542": "το",
+  "543": "ού",
+  "544": "▁του",
+  "545": "▁προ",
+  "546": "▁με",
+  "547": "ζ",
+  "548": "▁θα",
+  "549": "▁είναι",
+  "550": "ρο",
+  "551": "ων",
+  "552": "μέ",
+  "553": "▁που",
+  "554": "ια",
+  "555": "νο",
+  "556": "ική",
+  "557": "ών",
+  "558": "ρι",
+  "559": "θε",
+  "560": "Ε",
+  "561": "ρί",
+  "562": "▁ότι",
+  "563": "ουμε",
+  "564": "▁από",
+  "565": "λο",
+  "566": "ρά",
+  "567": "ιο",
+  "568": "▁των",
+  "569": "ευ",
+  "570": "λη",
+  "571": "ουν",
+  "572": "Α",
+  "573": "▁σε",
+  "574": "Π",
+  "575": "▁συν",
+  "576": "φορ",
+  "577": "▁δεν",
+  "578": "Σ",
+  "579": "▁στο",
+  "580": "▁δι",
+  "581": "τά",
+  "582": "▁αυτό",
+  "583": "▁δια",
+  "584": "ιστ",
+  "585": "▁πολύ",
+  "586": "▁πρέπει",
+  "587": "▁στην",
+  "588": "σουμε",
+  "589": "ικά",
+  "590": "Τ",
+  "591": "▁επ",
+  "592": "Κ",
+  "593": "ψ",
+  "594": "▁απο",
+  "595": "▁οι",
+  "596": "εται",
+  "597": "▁επι",
+  "598": "▁Υπότιτλοι",
+  "599": "▁AUTHORWAVE",
+  "600": "ούμε",
+  "601": "ικό",
+  "602": "▁Και",
+  "603": "πρό",
+  "604": "▁Ευχαριστώ",
+  "605": "▁μια",
+  "606": "▁ένα",
+  "607": "▁συμ",
+  "608": "Μ",
+  "609": "▁περι",
+  "610": "▁αυτή",
+  "611": "ήσει",
+  "612": "Ο",
+  "613": "ικέ",
+  "614": "▁κατά",
+  "615": "Γ",
+  "616": "Θ",
+  "617": "▁Ευρωπαϊκή",
+  "618": "▁έχουμε",
+  "619": "▁αλλά",
+  "620": "εργ",
+  "621": "Η",
+  "622": "▁θέμα",
+  "623": "ολογ",
+  "624": "ότητα",
+  "625": "▁έχει",
+  "626": "πολιτ",
+  "627": "Δ",
+  "628": "▁λοιπόν",
+  "629": "ονται",
+  "630": "Ν",
+  "631": "φέρ",
+  "632": "▁Επιτροπή",
+  "633": "▁αυτά",
+  "634": "▁Ένωση",
+  "635": "Υ",
+  "636": "ϊ",
+  "637": "▁Δεν",
+  "638": "▁έχουν",
+  "639": "▁υπάρχει",
+  "640": "Β",
+  "641": "Ι",
+  "642": "Λ",
+  "643": "Φ",
+  "644": "Ρ",
+  "645": "Χ",
+  "646": "Ξ",
+  "647": "Ω",
+  "648": "Ζ",
+  "649": "Ψ",
+  "650": "Ή",
+  "651": "Ά",
+  "652": "Ό",
+  "653": "Έ",
+  "654": "<et-EE>",
+  "655": "ma",
+  "656": "ta",
+  "657": "se",
+  "658": "da",
+  "659": "si",
+  "660": "▁on",
+  "661": "õ",
+  "662": "ks",
+  "663": "ga",
+  "664": "▁et",
+  "665": "▁ka",
+  "666": "he",
+  "667": "mu",
+  "668": "tu",
+  "669": "ha",
+  "670": "ja",
+  "671": "gi",
+  "672": "▁selle",
+  "673": "▁ole",
+  "674": "nd",
+  "675": "oo",
+  "676": "gu",
+  "677": "ju",
+  "678": "est",
+  "679": "▁ei",
+  "680": "▁pa",
+  "681": "nud",
+  "682": "▁väga",
+  "683": "▁see",
+  "684": "tud",
+  "685": "▁pea",
+  "686": "nda",
+  "687": "är",
+  "688": "▁Euroopa",
+  "689": "▁kui",
+  "690": "vad",
+  "691": "ke",
+  "692": "sta",
+  "693": "sed",
+  "694": "▁või",
+  "695": "di",
+  "696": "▁saa",
+  "697": "mise",
+  "698": "▁siis",
+  "699": "▁su",
+  "700": "ide",
+  "701": "pool",
+  "702": "val",
+  "703": "tus",
+  "704": "▁seda",
+  "705": "▁Me",
+  "706": "▁vastu",
+  "707": "▁jä",
+  "708": "▁tule",
+  "709": "selt",
+  "710": "ment",
+  "711": "▁kes",
+  "712": "ndus",
+  "713": "▁töö",
+  "714": "▁kõik",
+  "715": "dus",
+  "716": "▁mõ",
+  "717": "eeri",
+  "718": "▁meie",
+  "719": "▁meil",
+  "720": "▁ning",
+  "721": "võt",
+  "722": "▁mida",
+  "723": "▁arv",
+  "724": "▁See",
+  "725": "takse",
+  "726": "▁vaja",
+  "727": "▁osa",
+  "728": "õigus",
+  "729": "▁nende",
+  "730": "▁nüüd",
+  "731": "▁aasta",
+  "732": "tsiooni",
+  "733": "▁inim",
+  "734": "▁need",
+  "735": "tsus",
+  "736": "riigi",
+  "737": "▁täh",
+  "738": "▁Liidu",
+  "739": "▁välja",
+  "740": "Ä",
+  "741": "Õ",
+  "742": "ã",
+  "743": "Q",
+  "744": "ć",
+  "745": "ñ",
+  "746": "<fi-FI>",
+  "747": "tä",
+  "748": "ssa",
+  "749": "lla",
+  "750": "▁että",
+  "751": "ksi",
+  "752": "ty",
+  "753": "ki",
+  "754": "vä",
+  "755": "pa",
+  "756": "lle",
+  "757": "lu",
+  "758": "tta",
+  "759": "stä",
+  "760": "isi",
+  "761": "ise",
+  "762": "llä",
+  "763": "kin",
+  "764": "nä",
+  "765": "ään",
+  "766": "kse",
+  "767": "tte",
+  "768": "jä",
+  "769": "ttä",
+  "770": "ssä",
+  "771": "ista",
+  "772": "inen",
+  "773": "kä",
+  "774": "llis",
+  "775": "tö",
+  "776": "▁myös",
+  "777": "vu",
+  "778": "taan",
+  "779": "▁tämä",
+  "780": "▁voi",
+  "781": "utta",
+  "782": "iden",
+  "783": "nyt",
+  "784": "▁niin",
+  "785": "▁Kiitos",
+  "786": "▁ovat",
+  "787": "hän",
+  "788": "suu",
+  "789": "▁toimi",
+  "790": "aika",
+  "791": "▁Tämä",
+  "792": "▁pää",
+  "793": "▁mutta",
+  "794": "▁käy",
+  "795": "▁tässä",
+  "796": "▁asia",
+  "797": "▁Tä",
+  "798": "▁jotka",
+  "799": "▁työ",
+  "800": "neet",
+  "801": "▁täytyy",
+  "802": "▁sitten",
+  "803": "▁Euroopan",
+  "804": "▁puolesta",
+  "805": "▁halua",
+  "806": "▁siitä",
+  "807": "▁komissio",
+  "808": "▁hyvä",
+  "809": "▁hyvin",
+  "810": "▁puhu",
+  "811": "▁meidän",
+  "812": "▁vastaan",
+  "813": "▁tärkeä",
+  "814": "▁kaikki",
+  "815": "▁Kiitoksia",
+  "816": "▁vielä",
+  "817": "▁muut",
+  "818": "▁paljon",
+  "819": "mahdollis",
+  "820": "parlament",
+  "821": "▁pitäisi",
+  "822": "▁hyväksy",
+  "823": "▁puheenjohtaja",
+  "824": "▁liitty",
+  "825": "ā",
+  "826": "ī",
+  "827": "ē",
+  "828": "ë",
+  "829": "<fr-FR>",
+  "830": "▁est",
+  "831": "▁c",
+  "832": "▁d",
+  "833": "▁la",
+  "834": "▁p",
+  "835": "▁que",
+  "836": "▁en",
+  "837": "▁le",
+  "838": "▁à",
+  "839": "es",
+  "840": "▁l",
+  "841": "▁un",
+  "842": "▁pas",
+  "843": "▁les",
+  "844": "▁qui",
+  "845": "▁il",
+  "846": "▁vous",
+  "847": "▁des",
+  "848": "▁ce",
+  "849": "▁qu",
+  "850": "▁pour",
+  "851": "▁n",
+  "852": "▁par",
+  "853": "▁ça",
+  "854": "▁une",
+  "855": "▁b",
+  "856": "ant",
+  "857": "▁j",
+  "858": "ais",
+  "859": "ez",
+  "860": "▁dans",
+  "861": "▁va",
+  "862": "▁C",
+  "863": "tre",
+  "864": "ir",
+  "865": "elle",
+  "866": "eur",
+  "867": "▁sur",
+  "868": "▁re",
+  "869": "▁con",
+  "870": "▁ma",
+  "871": "▁Et",
+  "872": "▁au",
+  "873": "ement",
+  "874": "tion",
+  "875": "té",
+  "876": "▁tout",
+  "877": "mp",
+  "878": "ique",
+  "879": "▁plus",
+  "880": "eux",
+  "881": "▁dé",
+  "882": "▁fait",
+  "883": "qu",
+  "884": "▁ai",
+  "885": "▁comme",
+  "886": "ens",
+  "887": "ac",
+  "888": "▁là",
+  "889": "▁si",
+  "890": "ait",
+  "891": "che",
+  "892": "▁mais",
+  "893": "que",
+  "894": "ul",
+  "895": "▁avec",
+  "896": "▁bien",
+  "897": "▁tu",
+  "898": "age",
+  "899": "▁mon",
+  "900": "▁Donc",
+  "901": "end",
+  "902": "▁faire",
+  "903": "▁être",
+  "904": "ver",
+  "905": "▁peu",
+  "906": "▁même",
+  "907": "tra",
+  "908": "cha",
+  "909": "▁nous",
+  "910": "▁donc",
+  "911": "▁sont",
+  "912": "▁moi",
+  "913": "ille",
+  "914": "ff",
+  "915": "▁ex",
+  "916": "ien",
+  "917": "▁Il",
+  "918": "▁très",
+  "919": "▁cette",
+  "920": "im",
+  "921": "ité",
+  "922": "▁dire",
+  "923": "▁peut",
+  "924": "ance",
+  "925": "aire",
+  "926": "mé",
+  "927": "▁app",
+  "928": "▁aussi",
+  "929": "▁petit",
+  "930": "aux",
+  "931": "▁parce",
+  "932": "onne",
+  "933": "mb",
+  "934": "man",
+  "935": "▁On",
+  "936": "▁quand",
+  "937": "▁autre",
+  "938": "ô",
+  "939": "▁chose",
+  "940": "▁puis",
+  "941": "▁était",
+  "942": "ndre",
+  "943": "port",
+  "944": "▁vraiment",
+  "945": "ence",
+  "946": "▁Mais",
+  "947": "î",
+  "948": "▁avoir",
+  "949": "form",
+  "950": "▁faut",
+  "951": "▁Alors",
+  "952": "ign",
+  "953": "▁où",
+  "954": "près",
+  "955": "▁beaucoup",
+  "956": "ture",
+  "957": "û",
+  "958": "Ç",
+  "959": "â",
+  "960": "ù",
+  "961": "<hu-HU>",
+  "962": "sz",
+  "963": "▁az",
+  "964": "▁hogy",
+  "965": "ő",
+  "966": "ás",
+  "967": "ok",
+  "968": "gy",
+  "969": "ek",
+  "970": "ál",
+  "971": "és",
+  "972": "em",
+  "973": "ár",
+  "974": "▁meg",
+  "975": "▁és",
+  "976": "▁is",
+  "977": "▁ez",
+  "978": "▁egy",
+  "979": "os",
+  "980": "ak",
+  "981": "ban",
+  "982": "nak",
+  "983": "ít",
+  "984": "ik",
+  "985": "unk",
+  "986": "▁nem",
+  "987": "oz",
+  "988": "ül",
+  "989": "án",
+  "990": "át",
+  "991": "cs",
+  "992": "él",
+  "993": "ér",
+  "994": "nek",
+  "995": "▁mi",
+  "996": "szer",
+  "997": "bb",
+  "998": "▁Köszönöm",
+  "999": "ség",
+  "1000": "▁kell",
+  "1001": "én",
+  "1002": "hat",
+  "1003": "▁ha",
+  "1004": "ság",
+  "1005": "▁szépen",
+  "1006": "ért",
+  "1007": "ék",
+  "1008": "ott",
+  "1009": "ön",
+  "1010": "ép",
+  "1011": "elő",
+  "1012": "ünk",
+  "1013": "▁van",
+  "1014": "▁ki",
+  "1015": "▁fel",
+  "1016": "ény",
+  "1017": "vé",
+  "1018": "leg",
+  "1019": "eket",
+  "1020": "▁Az",
+  "1021": "juk",
+  "1022": "▁köz",
+  "1023": "ű",
+  "1024": "▁nagyon",
+  "1025": "▁tud",
+  "1026": "▁jelen",
+  "1027": "▁amely",
+  "1028": "▁lehet",
+  "1029": "▁ami",
+  "1030": "▁kérdés",
+  "1031": "▁ellen",
+  "1032": "tart",
+  "1033": "ről",
+  "1034": "É",
+  "1035": "ország",
+  "1036": "rend",
+  "1037": "ról",
+  "1038": "▁vagy",
+  "1039": "▁fontos",
+  "1040": "▁Európai",
+  "1041": "▁akkor",
+  "1042": "▁jog",
+  "1043": "▁fog",
+  "1044": "fogad",
+  "1045": "kapcsol",
+  "1046": "▁rész",
+  "1047": "áció",
+  "1048": "▁volt",
+  "1049": "▁elnök",
+  "1050": "▁bizottság",
+  "1051": "▁gondol",
+  "1052": "▁olyan",
+  "1053": "▁illetve",
+  "1054": "▁tagállam",
+  "1055": "▁pedig",
+  "1056": "▁Tehát",
+  "1057": "▁európai",
+  "1058": "▁szükség",
+  "1059": "szavaz",
+  "1060": "▁tehát",
+  "1061": "következ",
+  "1062": "▁össze",
+  "1063": "▁biztos",
+  "1064": "Ö",
+  "1065": "Á",
+  "1066": "Í",
+  "1067": "Ő",
+  "1068": "<hr-HR>",
+  "1069": "▁u",
+  "1070": "▁bi",
+  "1071": "▁sa",
+  "1072": "će",
+  "1073": "▁od",
+  "1074": "ru",
+  "1075": "▁iz",
+  "1076": "go",
+  "1077": "nje",
+  "1078": "sti",
+  "1079": "đ",
+  "1080": "▁pri",
+  "1081": "ima",
+  "1082": "nu",
+  "1083": "▁pre",
+  "1084": "▁Hvala",
+  "1085": "lje",
+  "1086": "▁što",
+  "1087": "či",
+  "1088": "nja",
+  "1089": "zi",
+  "1090": "vr",
+  "1091": "ći",
+  "1092": "če",
+  "1093": "ca",
+  "1094": "▁koji",
+  "1095": "ba",
+  "1096": "▁raz",
+  "1097": "ț",
+  "1098": "<it-IT>",
+  "1099": "▁di",
+  "1100": "▁e",
+  "1101": "▁che",
+  "1102": "▁è",
+  "1103": "co",
+  "1104": "▁per",
+  "1105": "▁al",
+  "1106": "▁non",
+  "1107": "do",
+  "1108": "gli",
+  "1109": "so",
+  "1110": "amo",
+  "1111": "sa",
+  "1112": "ndo",
+  "1113": "▁una",
+  "1114": "fi",
+  "1115": "pi",
+  "1116": "nti",
+  "1117": "tto",
+  "1118": "tro",
+  "1119": "▁fa",
+  "1120": "chi",
+  "1121": "▁qua",
+  "1122": "zione",
+  "1123": "bi",
+  "1124": "▁del",
+  "1125": "mente",
+  "1126": "pe",
+  "1127": "ssi",
+  "1128": "▁ri",
+  "1129": "▁sono",
+  "1130": "▁me",
+  "1131": "▁questo",
+  "1132": "nte",
+  "1133": "tti",
+  "1134": "tà",
+  "1135": "▁nel",
+  "1136": "▁anche",
+  "1137": "sso",
+  "1138": "▁perché",
+  "1139": "▁più",
+  "1140": "nta",
+  "1141": "▁come",
+  "1142": "cu",
+  "1143": "▁quindi",
+  "1144": "ggi",
+  "1145": "nza",
+  "1146": "sto",
+  "1147": "▁ho",
+  "1148": "ò",
+  "1149": "▁della",
+  "1150": "gra",
+  "1151": "▁fare",
+  "1152": "spe",
+  "1153": "cco",
+  "1154": "nde",
+  "1155": "mento",
+  "1156": "fe",
+  "1157": "gio",
+  "1158": "pu",
+  "1159": "▁questa",
+  "1160": "▁tra",
+  "1161": "zza",
+  "1162": "sci",
+  "1163": "▁ba",
+  "1164": "▁dei",
+  "1165": "▁poi",
+  "1166": "sco",
+  "1167": "stra",
+  "1168": "▁quel",
+  "1169": "qui",
+  "1170": "▁delle",
+  "1171": "▁cosa",
+  "1172": "▁molto",
+  "1173": "sse",
+  "1174": "zioni",
+  "1175": "▁vol",
+  "1176": "▁inter",
+  "1177": "sce",
+  "1178": "▁fatto",
+  "1179": "▁com",
+  "1180": "▁quello",
+  "1181": "▁essere",
+  "1182": "▁due",
+  "1183": "▁abbiamo",
+  "1184": "▁comp",
+  "1185": "▁tutti",
+  "1186": "ì",
+  "1187": "▁prima",
+  "1188": "▁parte",
+  "1189": "▁così",
+  "1190": "▁sempre",
+  "1191": "▁tutto",
+  "1192": "▁video",
+  "1193": "▁maglia",
+  "1194": "▁imp",
+  "1195": "▁cui",
+  "1196": "▁dove",
+  "1197": "▁col",
+  "1198": "▁Quindi",
+  "1199": "sione",
+  "1200": "rebbe",
+  "1201": "scri",
+  "1202": "<lt-LT>",
+  "1203": "ė",
+  "1204": "ai",
+  "1205": "ų",
+  "1206": "▁ir",
+  "1207": "as",
+  "1208": "į",
+  "1209": "▁kad",
+  "1210": "ės",
+  "1211": "▁tai",
+  "1212": "ū",
+  "1213": "tų",
+  "1214": "▁yra",
+  "1215": "ių",
+  "1216": "uo",
+  "1217": "▁ko",
+  "1218": "▁iš",
+  "1219": "tin",
+  "1220": "▁vis",
+  "1221": "čia",
+  "1222": "▁kuri",
+  "1223": "dė",
+  "1224": "ly",
+  "1225": "gal",
+  "1226": "▁ši",
+  "1227": "iau",
+  "1228": "jo",
+  "1229": "tar",
+  "1230": "yb",
+  "1231": "▁Ir",
+  "1232": "▁tik",
+  "1233": "ijos",
+  "1234": "sak",
+  "1235": "▁turi",
+  "1236": "oje",
+  "1237": "▁Tai",
+  "1238": "jų",
+  "1239": "▁apie",
+  "1240": "▁nu",
+  "1241": "▁mes",
+  "1242": "▁už",
+  "1243": "išk",
+  "1244": "▁gali",
+  "1245": "▁dėl",
+  "1246": "▁labai",
+  "1247": "imas",
+  "1248": "klaus",
+  "1249": "laik",
+  "1250": "▁Europos",
+  "1251": "▁aš",
+  "1252": "veik",
+  "1253": "▁būtų",
+  "1254": "darb",
+  "1255": "▁kaip",
+  "1256": "▁teis",
+  "1257": "▁daug",
+  "1258": "▁tikrai",
+  "1259": "▁pra",
+  "1260": "reik",
+  "1261": "▁buvo",
+  "1262": "turė",
+  "1263": "▁valstyb",
+  "1264": "▁reikia",
+  "1265": "▁būti",
+  "1266": "▁Aš",
+  "1267": "▁mūsų",
+  "1268": "▁jūs",
+  "1269": "vyk",
+  "1270": "▁Ačiū",
+  "1271": "cija",
+  "1272": "Į",
+  "1273": "ņ",
+  "1274": "<lv-LV>",
+  "1275": "▁no",
+  "1276": "jā",
+  "1277": "iem",
+  "1278": "tā",
+  "1279": "āk",
+  "1280": "▁ar",
+  "1281": "ām",
+  "1282": "▁pie",
+  "1283": "ies",
+  "1284": "ot",
+  "1285": "kā",
+  "1286": "ļ",
+  "1287": "tr",
+  "1288": "▁tā",
+  "1289": "īt",
+  "1290": "nā",
+  "1291": "▁uz",
+  "1292": "▁tas",
+  "1293": "ēt",
+  "1294": "dz",
+  "1295": "▁arī",
+  "1296": "▁vien",
+  "1297": "▁jau",
+  "1298": "▁kā",
+  "1299": "▁ie",
+  "1300": "gad",
+  "1301": "▁kur",
+  "1302": "▁kas",
+  "1303": "▁Un",
+  "1304": "▁mēs",
+  "1305": "iet",
+  "1306": "dā",
+  "1307": "īg",
+  "1308": "▁Ta",
+  "1309": "▁kād",
+  "1310": "kaut",
+  "1311": "ēm",
+  "1312": "▁lie",
+  "1313": "umu",
+  "1314": "ties",
+  "1315": "dar",
+  "1316": "lē",
+  "1317": "▁vai",
+  "1318": "▁bija",
+  "1319": "▁mums",
+  "1320": "▁tad",
+  "1321": "▁bet",
+  "1322": "ība",
+  "1323": "▁ga",
+  "1324": "▁Latvijas",
+  "1325": "ija",
+  "1326": "kr",
+  "1327": "vē",
+  "1328": "sim",
+  "1329": "▁šo",
+  "1330": "dien",
+  "1331": "gan",
+  "1332": "īgi",
+  "1333": "▁ap",
+  "1334": "ģ",
+  "1335": "▁būt",
+  "1336": "domā",
+  "1337": "▁tev",
+  "1338": "mēr",
+  "1339": "▁daudz",
+  "1340": "▁aiz",
+  "1341": "▁Tā",
+  "1342": "▁tād",
+  "1343": "▁tur",
+  "1344": "▁monēt",
+  "1345": "▁vēl",
+  "1346": "▁laik",
+  "1347": "▁cilvē",
+  "1348": "▁nav",
+  "1349": "▁lab",
+  "1350": "▁ļoti",
+  "1351": "aug",
+  "1352": "▁līdz",
+  "1353": "▁lai",
+  "1354": "šana",
+  "1355": "▁Nu",
+  "1356": "▁viņa",
+  "1357": "▁savu",
+  "1358": "▁cit",
+  "1359": "teik",
+  "1360": "▁darb",
+  "1361": "▁Ne",
+  "1362": "zin",
+  "1363": "▁pirm",
+  "1364": "▁Latvi",
+  "1365": "▁tieš",
+  "1366": "▁viņi",
+  "1367": "ēja",
+  "1368": "dzīvo",
+  "1369": "▁viņš",
+  "1370": "▁pilsē",
+  "1371": "ināt",
+  "1372": "▁viņu",
+  "1373": "▁tagad",
+  "1374": "kārt",
+  "1375": "▁pats",
+  "1376": "▁vairāk",
+  "1377": "reiz",
+  "1378": "▁tikai",
+  "1379": "sakta",
+  "1380": "▁bij",
+  "1381": "▁Viņ",
+  "1382": "▁sev",
+  "1383": "▁māj",
+  "1384": "vērt",
+  "1385": "▁20",
+  "1386": "▁ceļ",
+  "1387": "tiek",
+  "1388": "iski",
+  "1389": "▁dzīv",
+  "1390": "▁kāpēc",
+  "1391": "▁Bet",
+  "1392": "▁pēc",
+  "1393": "▁nozīmē",
+  "1394": "niek",
+  "1395": "ībā",
+  "1396": "▁palīdz",
+  "1397": "▁protams",
+  "1398": "▁stils",
+  "1399": "▁vajadz",
+  "1400": "▁attīstī",
+  "1401": "▁svarīg",
+  "1402": "▁sievie",
+  "1403": "▁grib",
+  "1404": "▁dažād",
+  "1405": "▁valst",
+  "1406": "▁banka",
+  "1407": "▁iespēja",
+  "1408": "▁bez",
+  "1409": "prāt",
+  "1410": "vērtīb",
+  "1411": "▁person",
+  "1412": "pasaules",
+  "1413": "▁varbūt",
+  "1414": "▁vienkārši",
+  "1415": "▁nauda",
+  "1416": "meklē",
+  "1417": "brauc",
+  "1418": "▁nevar",
+  "1419": "ācijas",
+  "1420": "spēj",
+  "1421": "ķ",
+  "1422": "<nl-NL>",
+  "1423": "▁een",
+  "1424": "▁het",
+  "1425": "▁dat",
+  "1426": "▁we",
+  "1427": "▁ik",
+  "1428": "ij",
+  "1429": "▁En",
+  "1430": "▁te",
+  "1431": "▁ook",
+  "1432": "▁niet",
+  "1433": "▁dan",
+  "1434": "▁zo",
+  "1435": "▁voor",
+  "1436": "▁met",
+  "1437": "▁aan",
+  "1438": "▁zijn",
+  "1439": "▁Ik",
+  "1440": "▁wel",
+  "1441": "▁wat",
+  "1442": "aar",
+  "1443": "▁ze",
+  "1444": "ken",
+  "1445": "▁heb",
+  "1446": "der",
+  "1447": "ui",
+  "1448": "den",
+  "1449": "▁daar",
+  "1450": "▁maar",
+  "1451": "op",
+  "1452": "▁heel",
+  "1453": "▁nog",
+  "1454": "▁Dus",
+  "1455": "oor",
+  "1456": "▁hebben",
+  "1457": "▁uit",
+  "1458": "▁of",
+  "1459": "ven",
+  "1460": "▁Maar",
+  "1461": "▁Dat",
+  "1462": "▁gaan",
+  "1463": "elijk",
+  "1464": "▁naar",
+  "1465": "▁moet",
+  "1466": "acht",
+  "1467": "▁waar",
+  "1468": "▁dus",
+  "1469": "▁ben",
+  "1470": "▁goed",
+  "1471": "▁Het",
+  "1472": "▁even",
+  "1473": "ond",
+  "1474": "eld",
+  "1475": "▁dit",
+  "1476": "▁wil",
+  "1477": "rij",
+  "1478": "▁echt",
+  "1479": "▁doen",
+  "1480": "▁gewoon",
+  "1481": "lijk",
+  "1482": "tijd",
+  "1483": "▁meer",
+  "1484": "▁mijn",
+  "1485": "▁We",
+  "1486": "▁gaat",
+  "1487": "werk",
+  "1488": "▁hoe",
+  "1489": "uw",
+  "1490": "▁eigenlijk",
+  "1491": "▁deze",
+  "1492": "zelf",
+  "1493": "vol",
+  "1494": "▁veel",
+  "1495": "atie",
+  "1496": "▁kunnen",
+  "1497": "▁door",
+  "1498": "llen",
+  "1499": "▁mee",
+  "1500": "▁onder",
+  "1501": "▁toe",
+  "1502": "▁zit",
+  "1503": "▁mensen",
+  "1504": "▁hij",
+  "1505": "▁denk",
+  "1506": "▁zie",
+  "1507": "▁heeft",
+  "1508": "▁kl",
+  "1509": "nnen",
+  "1510": "▁zien",
+  "1511": "komen",
+  "1512": "▁natuurlijk",
+  "1513": "heid",
+  "1514": "▁Dan",
+  "1515": "▁vind",
+  "1516": "▁wordt",
+  "1517": "▁iets",
+  "1518": "▁maken",
+  "1519": "▁doe",
+  "1520": "▁Wat",
+  "1521": "▁wij",
+  "1522": "▁beetje",
+  "1523": "▁worden",
+  "1524": "▁Want",
+  "1525": "▁twee",
+  "1526": "▁hem",
+  "1527": "▁had",
+  "1528": "▁jullie",
+  "1529": "▁Als",
+  "1530": "▁kijken",
+  "1531": "▁toch",
+  "1532": "▁tot",
+  "1533": "nieuw",
+  "1534": "lang",
+  "1535": "▁Nou",
+  "1536": "▁krijg",
+  "1537": "houd",
+  "1538": "▁hele",
+  "1539": "▁allemaal",
+  "1540": "▁want",
+  "1541": "▁zeggen",
+  "1542": "▁leuk",
+  "1543": "<pl-PL>",
+  "1544": "nie",
+  "1545": "▁w",
+  "1546": "cz",
+  "1547": "wa",
+  "1548": "▁się",
+  "1549": "▁jest",
+  "1550": "my",
+  "1551": "ła",
+  "1552": "cie",
+  "1553": "czy",
+  "1554": "▁nie",
+  "1555": "wie",
+  "1556": "▁wy",
+  "1557": "nia",
+  "1558": "wo",
+  "1559": "rze",
+  "1560": "ło",
+  "1561": "▁że",
+  "1562": "dzi",
+  "1563": "ej",
+  "1564": "ów",
+  "1565": "dzie",
+  "1566": "▁prze",
+  "1567": "ści",
+  "1568": "by",
+  "1569": "za",
+  "1570": "dy",
+  "1571": "ry",
+  "1572": "ń",
+  "1573": "ją",
+  "1574": "we",
+  "1575": "cze",
+  "1576": "owa",
+  "1577": "ego",
+  "1578": "że",
+  "1579": "cy",
+  "1580": "rzy",
+  "1581": "mie",
+  "1582": "▁przy",
+  "1583": "ły",
+  "1584": "rz",
+  "1585": "szy",
+  "1586": "sze",
+  "1587": "ść",
+  "1588": "wia",
+  "1589": "zy",
+  "1590": "ży",
+  "1591": "▁tutaj",
+  "1592": "ję",
+  "1593": "pie",
+  "1594": "nych",
+  "1595": "▁tym",
+  "1596": "▁może",
+  "1597": "cji",
+  "1598": "▁pod",
+  "1599": "▁ale",
+  "1600": "▁tego",
+  "1601": "owy",
+  "1602": "uje",
+  "1603": "▁bo",
+  "1604": "▁był",
+  "1605": "ną",
+  "1606": "bie",
+  "1607": "sy",
+  "1608": "▁też",
+  "1609": "▁bardzo",
+  "1610": "▁są",
+  "1611": "▁będzie",
+  "1612": "▁Po",
+  "1613": "ski",
+  "1614": "▁które",
+  "1615": "ź",
+  "1616": "▁już",
+  "1617": "▁dla",
+  "1618": "łem",
+  "1619": "nego",
+  "1620": "▁Nie",
+  "1621": "▁No",
+  "1622": "▁praw",
+  "1623": "cja",
+  "1624": "▁ten",
+  "1625": "▁takie",
+  "1626": "ować",
+  "1627": "▁który",
+  "1628": "▁właśnie",
+  "1629": "▁jeszcze",
+  "1630": "▁tam",
+  "1631": "▁żeby",
+  "1632": "▁być",
+  "1633": "▁więc",
+  "1634": "▁czyli",
+  "1635": "▁sobie",
+  "1636": "▁sam",
+  "1637": "▁tylko",
+  "1638": "▁tej",
+  "1639": "▁spraw",
+  "1640": "▁Na",
+  "1641": "▁mówi",
+  "1642": "▁osob",
+  "1643": "▁czas",
+  "1644": "▁prac",
+  "1645": "▁Czy",
+  "1646": "▁prostu",
+  "1647": "▁teraz",
+  "1648": "stęp",
+  "1649": "▁Was",
+  "1650": "▁myśl",
+  "1651": "▁powiedz",
+  "1652": "▁zrobi",
+  "1653": "liśmy",
+  "1654": "▁jakieś",
+  "1655": "ając",
+  "1656": "▁widz",
+  "1657": "▁kart",
+  "1658": "▁musi",
+  "1659": "▁pyta",
+  "1660": "<pt-BR>",
+  "1661": "pt",
+  "1662": "PT",
+  "1663": "<",
+  "1664": ">",
+  "1665": "-",
+  "1666": "▁é",
+  "1667": "▁não",
+  "1668": "▁eu",
+  "1669": "▁um",
+  "1670": "▁você",
+  "1671": "▁para",
+  "1672": "ão",
+  "1673": "▁aqui",
+  "1674": "▁uma",
+  "1675": "ção",
+  "1676": "▁ca",
+  "1677": "▁pe",
+  "1678": "▁tem",
+  "1679": "▁em",
+  "1680": "▁gente",
+  "1681": "▁O",
+  "1682": "▁ele",
+  "1683": "pre",
+  "1684": "ria",
+  "1685": "▁fo",
+  "1686": "mos",
+  "1687": "nho",
+  "1688": "▁Então",
+  "1689": "bo",
+  "1690": "io",
+  "1691": "nha",
+  "1692": "▁isso",
+  "1693": "▁por",
+  "1694": "▁muito",
+  "1695": "nto",
+  "1696": "▁Eu",
+  "1697": "▁está",
+  "1698": "idade",
+  "1699": "▁aí",
+  "1700": "be",
+  "1701": "▁esse",
+  "1702": "▁pode",
+  "1703": "▁como",
+  "1704": "ente",
+  "1705": "▁também",
+  "1706": "▁essa",
+  "1707": "lha",
+  "1708": "▁já",
+  "1709": "▁mas",
+  "1710": "▁pessoa",
+  "1711": "qua",
+  "1712": "▁né",
+  "1713": "▁fazer",
+  "1714": "▁tá",
+  "1715": "lho",
+  "1716": "▁lá",
+  "1717": "fica",
+  "1718": "▁vou",
+  "1719": "▁porque",
+  "1720": "▁Se",
+  "1721": "▁fala",
+  "1722": "▁coisa",
+  "1723": "▁Não",
+  "1724": "...",
+  "1725": "▁só",
+  "1726": "▁nós",
+  "1727": "ço",
+  "1728": "▁Por",
+  "1729": "▁assim",
+  "1730": "▁Co",
+  "1731": "iza",
+  "1732": "▁bem",
+  "1733": "▁todo",
+  "1734": "eira",
+  "1735": "▁sua",
+  "1736": "ência",
+  "1737": "ções",
+  "1738": "▁Você",
+  "1739": "▁tudo",
+  "1740": "▁agora",
+  "1741": "eiro",
+  "1742": "ário",
+  "1743": "▁até",
+  "1744": "▁mesmo",
+  "1745": "▁vamos",
+  "1746": "▁quando",
+  "1747": "ciona",
+  "1748": "<ro-RO>",
+  "1749": "▁în",
+  "1750": "ți",
+  "1751": "▁să",
+  "1752": "▁și",
+  "1753": "▁cu",
+  "1754": "▁că",
+  "1755": "▁care",
+  "1756": "▁mai",
+  "1757": "ră",
+  "1758": "sc",
+  "1759": "că",
+  "1760": "▁am",
+  "1761": "are",
+  "1762": "▁din",
+  "1763": "▁fi",
+  "1764": "▁este",
+  "1765": "tă",
+  "1766": "▁pentru",
+  "1767": "rea",
+  "1768": "ști",
+  "1769": "ș",
+  "1770": "ele",
+  "1771": "du",
+  "1772": "▁M",
+  "1773": "▁fac",
+  "1774": "ân",
+  "1775": "▁sunt",
+  "1776": "▁I",
+  "1777": "▁acest",
+  "1778": "ului",
+  "1779": "lor",
+  "1780": "▁mult",
+  "1781": "și",
+  "1782": "▁mo",
+  "1783": "▁fost",
+  "1784": "per",
+  "1785": "▁foarte",
+  "1786": "▁Și",
+  "1787": "▁mă",
+  "1788": "să",
+  "1789": "cur",
+  "1790": "tor",
+  "1791": "▁cum",
+  "1792": "inte",
+  "1793": "ată",
+  "1794": "ște",
+  "1795": "▁dacă",
+  "1796": "ând",
+  "1797": "▁subliniere",
+  "1798": "▁dar",
+  "1799": "▁sau",
+  "1800": "tat",
+  "1801": "ori",
+  "1802": "▁vă",
+  "1803": "▁asta",
+  "1804": "nă",
+  "1805": "▁prim",
+  "1806": "▁așa",
+  "1807": "ează",
+  "1808": "▁într",
+  "1809": "▁spun",
+  "1810": "▁lui",
+  "1811": "▁sub",
+  "1812": "itate",
+  "1813": "▁aici",
+  "1814": "▁bine",
+  "1815": "▁când",
+  "1816": "▁prin",
+  "1817": "▁alt",
+  "1818": "▁nici",
+  "1819": "stru",
+  "1820": "▁cât",
+  "1821": "▁vede",
+  "1822": "fer",
+  "1823": "▁după",
+  "1824": "▁ju",
+  "1825": "▁despre",
+  "1826": "▁timp",
+  "1827": "▁acum",
+  "1828": "▁poate",
+  "1829": "▁spus",
+  "1830": "▁lucru",
+  "1831": "▁făcut",
+  "1832": "păr",
+  "1833": "▁urmă",
+  "1834": "▁atunci",
+  "1835": "▁fr",
+  "1836": "▁chiar",
+  "1837": "▁încep",
+  "1838": "Ș",
+  "1839": "Î",
+  "1840": "<ru-RU>",
+  "1841": "<sk-SK>",
+  "1842": "ov",
+  "1843": "ľ",
+  "1844": "sk",
+  "1845": "▁aj",
+  "1846": "ob",
+  "1847": "tá",
+  "1848": "ať",
+  "1849": "▁bol",
+  "1850": "▁sú",
+  "1851": "▁ako",
+  "1852": "ži",
+  "1853": "▁sme",
+  "1854": "▁V",
+  "1855": "ali",
+  "1856": "▁alebo",
+  "1857": "▁čo",
+  "1858": "iť",
+  "1859": "▁má",
+  "1860": "ých",
+  "1861": "▁zá",
+  "1862": "▁tie",
+  "1863": "▁nejak",
+  "1864": "▁vý",
+  "1865": "čas",
+  "1866": "nov",
+  "1867": "rov",
+  "1868": "▁ktoré",
+  "1869": "ajú",
+  "1870": "ovať",
+  "1871": "▁keď",
+  "1872": "▁str",
+  "1873": "▁škol",
+  "1874": "nú",
+  "1875": "▁ktor",
+  "1876": "▁vlastne",
+  "1877": "▁prí",
+  "1878": "nej",
+  "1879": "▁veľmi",
+  "1880": "šie",
+  "1881": "rob",
+  "1882": "▁tr",
+  "1883": "ných",
+  "1884": "enie",
+  "1885": "▁spo",
+  "1886": "▁rok",
+  "1887": "osti",
+  "1888": "▁tým",
+  "1889": "▁môže",
+  "1890": "▁ktorý",
+  "1891": "osť",
+  "1892": "▁projekt",
+  "1893": "▁kon",
+  "1894": "▁vzdeláva",
+  "1895": "▁Takže",
+  "1896": "▁ešte",
+  "1897": "▁tých",
+  "1898": "▁mal",
+  "1899": "▁cel",
+  "1900": "▁potom",
+  "1901": "▁svoj",
+  "1902": "enia",
+  "1903": "álne",
+  "1904": "ieť",
+  "1905": "▁teda",
+  "1906": "jedn",
+  "1907": "sled",
+  "1908": "▁možno",
+  "1909": "▁vám",
+  "1910": "chod",
+  "1911": "ujú",
+  "1912": "tvor",
+  "1913": "▁druh",
+  "1914": "▁Slovensk",
+  "1915": "hľad",
+  "1916": "stup",
+  "1917": "▁ľudí",
+  "1918": "▁napríklad",
+  "1919": "▁veľk",
+  "1920": "▁niečo",
+  "1921": "Ď",
+  "1922": "<sl-SL>",
+  "1923": "sl",
+  "1924": "lj",
+  "1925": "kot",
+  "1926": "ih",
+  "1927": "▁svet",
+  "1928": "▁ta",
+  "1929": "▁tako",
+  "1930": "▁kar",
+  "1931": "▁nek",
+  "1932": "jih",
+  "1933": "udi",
+  "1934": "▁vse",
+  "1935": "▁drug",
+  "1936": "▁ima",
+  "1937": "kaj",
+  "1938": "▁smo",
+  "1939": "del",
+  "1940": "▁sem",
+  "1941": "▁lahko",
+  "1942": "▁samo",
+  "1943": "▁več",
+  "1944": "nih",
+  "1945": "▁držav",
+  "1946": "▁zelo",
+  "1947": "▁zdaj",
+  "1948": "▁razum",
+  "1949": "▁še",
+  "1950": "▁tega",
+  "1951": "▁ljudi",
+  "1952": "▁pred",
+  "1953": "▁sta",
+  "1954": "nost",
+  "1955": "▁ampak",
+  "1956": "▁novinar",
+  "1957": "▁naprej",
+  "1958": "▁mora",
+  "1959": "▁Vs",
+  "1960": "krat",
+  "1961": "▁Ampak",
+  "1962": "▁vedno",
+  "1963": "▁velik",
+  "1964": "▁kako",
+  "1965": "▁najbolj",
+  "1966": "ziroma",
+  "1967": "▁vsi",
+  "1968": "▁nekaj",
+  "1969": "▁kater",
+  "1970": "▁res",
+  "1971": "▁tukaj",
+  "1972": "▁dogaja",
+  "1973": "▁svoje",
+  "1974": "▁let",
+  "1975": "daj",
+  "1976": "▁pripriča",
+  "1977": "▁človek",
+  "1978": "▁hoče",
+  "1979": "▁vojn",
+  "1980": "▁Pre",
+  "1981": "▁dobr",
+  "1982": "ljan",
+  "1983": "▁moj",
+  "1984": "▁dejansko",
+  "1985": "▁ljudje",
+  "1986": "▁mediji",
+  "1987": "▁prot",
+  "1988": "▁narav",
+  "1989": "bilo",
+  "1990": "▁Afrik",
+  "1991": "▁vzhod",
+  "1992": "▁človeštva",
+  "1993": "▁kriz",
+  "1994": "▁pogled",
+  "1995": "▁medije",
+  "1996": "poved",
+  "1997": "▁začel",
+  "1998": "▁večin",
+  "1999": "imajo",
+  "2000": "▁Ljudje",
+  "2001": "▁družb",
+  "2002": "▁govorim",
+  "2003": "▁informacij",
+  "2004": "▁kultur",
+  "2005": "▁bližnj",
+  "2006": "▁podobno",
+  "2007": "▁njihov",
+  "2008": "▁konc",
+  "2009": "▁pisa",
+  "2010": "▁zaveda",
+  "2011": "▁vsak",
+  "2012": "živel",
+  "2013": "▁funkcionira",
+  "2014": "▁internet",
+  "2015": "▁islamsk",
+  "2016": "▁film",
+  "2017": "▁otroci",
+  "2018": "▁prihaja",
+  "2019": "▁političn",
+  "2020": "▁popoln",
+  "2021": "▁Velik",
+  "2022": "▁drugačen",
+  "2023": "▁recimo",
+  "2024": "▁resnic",
+  "2025": "solutno",
+  "2026": "▁Bližn",
+  "2027": "▁Evropsk",
+  "2028": "▁muslimani",
+  "2029": "▁nadzoruje",
+  "2030": "▁socialne",
+  "2031": "▁zgodovin",
+  "2032": "▁človešk",
+  "2033": "▁življenj",
+  "2034": "▁prijatelj",
+  "2035": "▁vendar",
+  "2036": "▁ljudem",
+  "2037": "▁števil",
+  "2038": "▁Sirij",
+  "2039": "<sv-SE>",
+  "2040": "▁att",
+  "2041": "▁och",
+  "2042": "▁är",
+  "2043": "▁för",
+  "2044": "▁här",
+  "2045": "▁jag",
+  "2046": "än",
+  "2047": "▁till",
+  "2048": "▁h",
+  "2049": "▁inte",
+  "2050": "▁Och",
+  "2051": "▁av",
+  "2052": "▁om",
+  "2053": "▁ska",
+  "2054": "▁ut",
+  "2055": "▁ett",
+  "2056": "all",
+  "2057": "▁också",
+  "2058": "▁Jag",
+  "2059": "era",
+  "2060": "pp",
+  "2061": "▁upp",
+  "2062": "▁då",
+  "2063": "▁där",
+  "2064": "▁lite",
+  "2065": "år",
+  "2066": "sam",
+  "2067": "isk",
+  "2068": "het",
+  "2069": "för",
+  "2070": "▁kommer",
+  "2071": "▁vill",
+  "2072": "ör",
+  "2073": "erna",
+  "2074": "ande",
+  "2075": "sätt",
+  "2076": "▁finns",
+  "2077": "▁när",
+  "2078": "▁vara",
+  "2079": "ade",
+  "2080": "sök",
+  "2081": "▁hur",
+  "2082": "▁vad",
+  "2083": "bil",
+  "2084": "▁göra",
+  "2085": "▁får",
+  "2086": "verk",
+  "2087": "▁mycket",
+  "2088": "▁väl",
+  "2089": "kom",
+  "2090": "▁gör",
+  "2091": "▁ni",
+  "2092": "▁bara",
+  "2093": "▁från",
+  "2094": "ställ",
+  "2095": "▁väldigt",
+  "2096": "▁min",
+  "2097": "▁olika",
+  "2098": "▁alla",
+  "2099": "lev",
+  "2100": "▁fram",
+  "2101": "▁kanske",
+  "2102": "▁vår",
+  "2103": "▁tid",
+  "2104": "skap",
+  "2105": "håll",
+  "2106": "▁För",
+  "2107": "▁går",
+  "2108": "▁blir",
+  "2109": "▁under",
+  "2110": "▁lär",
+  "2111": "▁ny",
+  "2112": "▁Då",
+  "2113": "▁börja",
+  "2114": "rätt",
+  "2115": "▁över",
+  "2116": "▁oss",
+  "2117": "▁exempel",
+  "2118": "▁skulle",
+  "2119": "gång",
+  "2120": "▁kunna",
+  "2121": "▁andra",
+  "2122": "▁någon",
+  "2123": "▁jobba",
+  "2124": "land",
+  "2125": "▁något",
+  "2126": "▁behöver",
+  "2127": "▁säga",
+  "2128": "klar",
+  "2129": "▁många",
+  "2130": "▁skriv",
+  "2131": "▁använda",
+  "2132": "▁själv",
+  "2133": "▁samma",
+  "2134": "lägg",
+  "2135": "▁måste",
+  "2136": "▁efter",
+  "2137": "text",
+  "2138": "▁prata",
+  "2139": "▁klicka",
+  "2140": "▁hitta",
+  "2141": "▁tror",
+  "2142": "▁någonting",
+  "2143": "fråga",
+  "2144": "▁titta",
+  "2145": "▁tycker",
+  "2146": "▁ganska",
+  "2147": "▁jätte",
+  "2148": "▁Vad",
+  "2149": "▁genom",
+  "2150": "▁även",
+  "2151": "▁tänker",
+  "2152": "arbete",
+  "2153": "▁faktiskt",
+  "2154": "person",
+  "2155": "▁komma",
+  "2156": "bygg",
+  "2157": "<uk-UA>",
+  "2158": "<ar-AR>",
+  "2159": "؟",
+  "2160": "،",
+  "2161": "vy",
+  "2162": "▁byl",
+  "2163": "Ň",
+  "2164": "Ť",
+  "2165": "Ó",
+  "2166": "ær",
+  "2167": "▁blev",
+  "2168": "ft",
+  "2169": "lige",
+  "2170": "ved",
+  "2171": "'",
+  "2172": "Å",
+  "2173": "▁H",
+  "2174": "▁D",
+  "2175": "aus",
+  "2176": "▁N",
+  "2177": "▁Be",
+  "2178": "mm",
+  "2179": "ab",
+  "2180": "▁Er",
+  "2181": "ssen",
+  "2182": "hl",
+  "2183": "hn",
+  "2184": "ischen",
+  "2185": "▁wurde",
+  "2186": "rie",
+  "2187": "lei",
+  "2188": "▁An",
+  "2189": "▁Ein",
+  "2190": "etz",
+  "2191": "rau",
+  "2192": "ische",
+  "2193": "äh",
+  "2194": "▁mein",
+  "2195": "▁So",
+  "2196": "▁hatte",
+  "2197": "▁unter",
+  "2198": "▁Zu",
+  "2199": "▁ihn",
+  "2200": "▁Jahr",
+  "2201": "▁zwei",
+  "2202": "keit",
+  "2203": "▁ihm",
+  "2204": "▁Aus",
+  "2205": "<en-GB>",
+  "2206": "▁you",
+  "2207": "▁that",
+  "2208": "▁and",
+  "2209": "▁can",
+  "2210": "▁it",
+  "2211": "▁your",
+  "2212": "ed",
+  "2213": "▁Okay",
+  "2214": "▁just",
+  "2215": "ay",
+  "2216": "▁Yeah",
+  "2217": "▁with",
+  "2218": "th",
+  "2219": "▁Thank",
+  "2220": "▁thank",
+  "2221": "▁help",
+  "2222": "▁please",
+  "2223": "▁one",
+  "2224": "<blank>",
+  "2225": "ic",
+  "2226": "▁much",
+  "2227": "▁what",
+  "2228": "▁my",
+  "2229": "hi",
+  "2230": "▁will",
+  "2231": "▁would",
+  "2232": "▁if",
+  "2233": "▁two",
+  "2234": "▁this",
+  "2235": "▁he",
+  "2236": "▁go",
+  "2237": "▁all",
+  "2238": "▁Oh",
+  "2239": "▁like",
+  "2240": "▁very",
+  "2241": "▁The",
+  "2242": "▁today",
+  "2243": "▁not",
+  "2244": "▁yeah",
+  "2245": "▁take",
+  "2246": "ight",
+  "2247": "ex",
+  "2248": "▁Ok",
+  "2249": "▁seven",
+  "2250": "▁number",
+  "2251": "▁know",
+  "2252": "▁about",
+  "2253": "▁four",
+  "2254": "▁okay",
+  "2255": "▁name",
+  "2256": "▁And",
+  "2257": "▁five",
+  "2258": "▁How",
+  "2259": "▁account",
+  "2260": "▁any",
+  "2261": "▁three",
+  "2262": "▁could",
+  "2263": "▁up",
+  "2264": "▁get",
+  "2265": "▁phone",
+  "2266": "▁great",
+  "2267": "▁six",
+  "2268": "▁eight",
+  "2269": "▁now",
+  "2270": "▁nine",
+  "2271": "▁That",
+  "2272": "▁address",
+  "2273": "▁look",
+  "2274": "▁call",
+  "2275": "ill",
+  "2276": "▁You",
+  "2277": "▁but",
+  "2278": "▁got",
+  "2279": "▁don",
+  "2280": "▁email",
+  "2281": "▁calling",
+  "2282": "▁problem",
+  "2283": "▁right",
+  "2284": "▁good",
+  "2285": "▁well",
+  "2286": "▁out",
+  "2287": "▁What",
+  "2288": "▁how",
+  "2289": "▁really",
+  "2290": "▁anything",
+  "2291": "▁actually",
+  "2292": "▁from",
+  "2293": "▁think",
+  "2294": "▁time",
+  "2295": "▁some",
+  "2296": "▁ask",
+  "2297": "▁else",
+  "2298": "other",
+  "2299": "▁fine",
+  "2300": "able",
+  "2301": "▁Good",
+  "2302": "▁when",
+  "2303": "▁full",
+  "2304": "▁confirm",
+  "2305": "▁give",
+  "2306": "▁more",
+  "2307": "ever",
+  "2308": "▁month",
+  "2309": "▁information",
+  "2310": "▁sure",
+  "2311": "▁survey",
+  "2312": "▁sorry",
+  "2313": "▁send",
+  "2314": "▁through",
+  "2315": "▁check",
+  "2316": "▁long",
+  "2317": "▁birth",
+  "2318": "▁should",
+  "2319": "▁twenty",
+  "2320": "▁make",
+  "2321": "▁zero",
+  "2322": "ful",
+  "2323": "▁store",
+  "2324": "▁policy",
+  "2325": "▁back",
+  "2326": "▁again",
+  "2327": "▁first",
+  "2328": "▁Could",
+  "2329": "▁work",
+  "2330": "▁afternoon",
+  "2331": "▁after",
+  "2332": "▁insurance",
+  "2333": "▁customer",
+  "2334": "▁payment",
+  "2335": "▁question",
+  "2336": "▁receive",
+  "2337": "▁possible",
+  "2338": "▁moment",
+  "2339": "▁system",
+  "2340": "▁change",
+  "2341": "▁hundred",
+  "2342": "▁nineteen",
+  "2343": "<en-US>",
+  "2344": "▁.",
+  "2345": "▁,",
+  "2346": "▁st",
+  "2347": "▁are",
+  "2348": "ow",
+  "2349": "ive",
+  "2350": "ate",
+  "2351": "ad",
+  "2352": "ect",
+  "2353": "▁they",
+  "2354": "▁as",
+  "2355": "ng",
+  "2356": "ity",
+  "2357": "ther",
+  "2358": "act",
+  "2359": "ist",
+  "2360": "▁our",
+  "2361": "▁sp",
+  "2362": "ally",
+  "2363": "▁his",
+  "2364": "▁But",
+  "2365": "▁has",
+  "2366": "▁also",
+  "2367": "▁which",
+  "2368": "▁He",
+  "2369": "▁uh",
+  "2370": "day",
+  "2371": "▁people",
+  "2372": "▁who",
+  "2373": "▁thing",
+  "2374": "▁because",
+  "2375": "▁other",
+  "2376": "ough",
+  "2377": "▁part",
+  "2378": "▁say",
+  "2379": "▁year",
+  "2380": "side",
+  "2381": "\"",
+  "2382": "<es-ES>",
+  "2383": "▁y",
+  "2384": "▁el",
+  "2385": "ción",
+  "2386": "▁Es",
+  "2387": "res",
+  "2388": "▁los",
+  "2389": "▁La",
+  "2390": "dos",
+  "2391": "ía",
+  "2392": "▁El",
+  "2393": "▁las",
+  "2394": "▁más",
+  "2395": "men",
+  "2396": "ño",
+  "2397": "▁esta",
+  "2398": "idad",
+  "2399": "par",
+  "2400": "¿",
+  "2401": "ría",
+  "2402": "▁fue",
+  "2403": "rio",
+  "2404": "enta",
+  "2405": "ón",
+  "2406": "cho",
+  "2407": "ciones",
+  "2408": "ble",
+  "2409": "▁Ca",
+  "2410": "▁muy",
+  "2411": "▁también",
+  "2412": "▁tiene",
+  "2413": "ña",
+  "2414": "▁Su",
+  "2415": "▁pero",
+  "2416": "▁son",
+  "2417": "encia",
+  "2418": "sión",
+  "2419": "▁hay",
+  "2420": "▁puede",
+  "2421": "ncia",
+  "2422": "▁mucho",
+  "2423": "▁Si",
+  "2424": "▁pues",
+  "2425": "miento",
+  "2426": "▁Con",
+  "2427": "ones",
+  "2428": "ecto",
+  "2429": "iendo",
+  "2430": "▁día",
+  "2431": "▁sobre",
+  "2432": "▁primer",
+  "2433": "▁qué",
+  "2434": "▁gusta",
+  "2435": "▁San",
+  "2436": "▁hacer",
+  "2437": "cional",
+  "2438": "▁verdad",
+  "2439": "▁persona",
+  "2440": "▁pasa",
+  "2441": "▁mejor",
+  "2442": "quí",
+  "2443": "▁Fue",
+  "2444": "▁Com",
+  "2445": "▁ciudad",
+  "2446": "Ñ",
+  "2447": "<es-US>",
+  "2448": "cia",
+  "2449": "▁lo",
+  "2450": "▁Y",
+  "2451": "ron",
+  "2452": "les",
+  "2453": "▁mu",
+  "2454": "cio",
+  "2455": "▁yo",
+  "2456": "bu",
+  "2457": "▁sí",
+  "2458": "▁Pero",
+  "2459": "▁así",
+  "2460": "<fr-CA>",
+  "2461": "ré",
+  "2462": "ée",
+  "2463": "▁Les",
+  "2464": "nt",
+  "2465": "our",
+  "2466": "▁Ce",
+  "2467": "com",
+  "2468": "▁Elle",
+  "2469": "▁Cet",
+  "2470": "ux",
+  "2471": "ale",
+  "2472": "ier",
+  "2473": "ction",
+  "2474": "▁cha",
+  "2475": "▁pré",
+  "2476": "▁deux",
+  "2477": "if",
+  "2478": "lé",
+  "2479": "ère",
+  "2480": "ière",
+  "2481": "iste",
+  "2482": "▁parti",
+  "2483": "▁été",
+  "2484": "cette",
+  "2485": "avec",
+  "2486": "▁tou",
+  "2487": "jour",
+  "2488": "app",
+  "2489": "cul",
+  "2490": "▁égale",
+  "2491": "aine",
+  "2492": "gue",
+  "2493": "▁trè",
+  "2494": "▁nombre",
+  "2495": "▁étai",
+  "2496": "tout",
+  "2497": "▁grand",
+  "2498": "▁commun",
+  "2499": "Une",
+  "2500": "œ",
+  "2501": "ï",
+  "2502": "À",
+  "2503": "Œ",
+  "2504": "È",
+  "2505": "ō",
+  "2506": "ÿ",
+  "2507": "Ō",
+  "2508": "Ô",
+  "2509": "Ê",
+  "2510": "Â",
+  "2511": "▁m",
+  "2512": "av",
+  "2513": "ouv",
+  "2514": "êt",
+  "2515": "ois",
+  "2516": "pri",
+  "2517": "voir",
+  "2518": "sion",
+  "2519": "ix",
+  "2520": "ang",
+  "2521": "était",
+  "2522": "ard",
+  "2523": "aient",
+  "2524": "Ć",
+  "2525": "İ",
+  "2526": "Ù",
+  "2527": "Û",
+  "2528": "Ë",
+  "2529": "Ï",
+  "2530": "<he-IL>",
+  "2531": "<hi-IN>",
+  "2532": "।",
+  "2533": "!",
+  "2534": "Ì",
+  "2535": "<ja-JP>",
+  "2536": "▁。",
+  "2537": "▁、",
+  "2538": "▁々",
+  "2539": "〜",
+  "2540": "々",
+  "2541": "？",
+  "2542": "、",
+  "2543": "。",
+  "2544": "<ko-KR>",
+  "2545": "<nb-NO>",
+  "2546": "ene",
+  "2547": "▁ble",
+  "2548": "ikk",
+  "2549": "opp",
+  "2550": "▁Han",
+  "2551": "▁Den",
+  "2552": "unn",
+  "2553": "▁han",
+  "2554": "asjon",
+  "2555": "▁word",
+  "2556": "▁werd",
+  "2557": "<nn-NO>",
+  "2558": "eg",
+  "2559": "▁ikkje",
+  "2560": "▁bok",
+  "2561": "lik",
+  "2562": "▁eit",
+  "2563": "så",
+  "2564": "kk",
+  "2565": "▁nok",
+  "2566": "▁god",
+  "2567": "▁lese",
+  "2568": "dde",
+  "2569": "inga",
+  "2570": "▁denn",
+  "2571": "inn",
+  "2572": "kkje",
+  "2573": "dig",
+  "2574": "tid",
+  "2575": "▁bøke",
+  "2576": "ord",
+  "2577": "▁tru",
+  "2578": "skje",
+  "2579": "▁sei",
+  "2580": "ller",
+  "2581": "▁fle",
+  "2582": "skriv",
+  "2583": "▁heil",
+  "2584": "wy",
+  "2585": "Ś",
+  "2586": "Ł",
+  "2587": "Ź",
+  "2588": "Ż",
+  "2589": "car",
+  "2590": "tão",
+  "2591": "ia",
+  "2592": "▁foi",
+  "2593": "ito",
+  "2594": "ram",
+  "2595": "fa",
+  "2596": "▁meu",
+  "2597": "ça",
+  "2598": "▁dois",
+  "2599": "ação",
+  "2600": "▁ter",
+  "2601": "nça",
+  "2602": "▁compra",
+  "2603": "▁mil",
+  "2604": "▁minha",
+  "2605": "▁passa",
+  "2606": "▁casa",
+  "2607": "Ã",
+  "2608": "·",
+  "2609": "<pt-PT>",
+  "2610": "das",
+  "2611": "▁são",
+  "2612": "▁Pa",
+  "2613": "tura",
+  "2614": "▁ser",
+  "2615": "▁Ele",
+  "2616": "forma",
+  "2617": "▁Esta",
+  "2618": "ões",
+  "2619": "▁pelo",
+  "2620": "tua",
+  "2621": "▁pela",
+  "2622": "mar",
+  "2623": "▁Foi",
+  "2624": "▁foram",
+  "2625": "este",
+  "2626": "▁Um",
+  "2627": "▁São",
+  "2628": "▁entre",
+  "2629": "fun",
+  "2630": "agem",
+  "2631": "gua",
+  "2632": "▁Brasil",
+  "2633": "▁grande",
+  "2634": "icos",
+  "2635": "▁cidade",
+  "2636": "inda",
+  "2637": "▁Este",
+  "2638": "▁maior",
+  "2639": "▁brasileiro",
+  "2640": "▁município",
+  "2641": "▁nome",
+  "2642": "▁encontra",
+  "2643": "ambém",
+  "2644": "▁Sua",
+  "2645": "▁três",
+  "2646": "ska",
+  "2647": "var",
+  "2648": "<th-TH>",
+  "2649": "<tr-TR>",
+  "2650": "ş",
+  "2651": "ğ",
+  "2652": "ya",
+  "2653": "▁ve",
+  "2654": "lar",
+  "2655": "▁bir",
+  "2656": "lı",
+  "2657": "dı",
+  "2658": "ler",
+  "2659": "ye",
+  "2660": "sı",
+  "2661": "ları",
+  "2662": "leri",
+  "2663": "ında",
+  "2664": "tı",
+  "2665": "▁bu",
+  "2666": "lan",
+  "2667": "ara",
+  "2668": "▁Bu",
+  "2669": "inde",
+  "2670": "ını",
+  "2671": "yı",
+  "2672": "yo",
+  "2673": "dü",
+  "2674": "▁olarak",
+  "2675": "▁için",
+  "2676": "maktadır",
+  "2677": "arı",
+  "2678": "▁baş",
+  "2679": "Ş",
+  "2680": "Ğ",
+  "2681": "<zh-CN>",
+  "2682": "⁇",
+  "2683": "Ａ",
+  "2684": "，",
+  "2685": "<vi-VN>",
+  "2686": "▁t",
+  "2687": "▁đ",
+  "2688": "nh",
+  "2689": "▁th",
+  "2690": "▁ch",
+  "2691": "▁nh",
+  "2692": "▁kh",
+  "2693": "▁ng",
+  "2694": "▁g",
+  "2695": "ông",
+  "2696": "▁ph",
+  "2697": "▁r",
+  "2698": "▁gi",
+  "2699": "ời",
+  "2700": "ên",
+  "2701": "▁cá",
+  "2702": "▁và",
+  "2703": "▁có",
+  "2704": "iệ",
+  "2705": "ột",
+  "2706": "▁không",
+  "2707": "ôi",
+  "2708": "iế",
+  "2709": "▁một",
+  "2710": "ới",
+  "2711": "ủa",
+  "2712": "▁của",
+  "2713": "▁x",
+  "2714": "ười",
+  "2715": "ượ",
+  "2716": "ình",
+  "2717": "ất",
+  "2718": "ại",
+  "2719": "uy",
+  "2720": "ày",
+  "2721": "▁người",
+  "2722": "ong",
+  "2723": "anh",
+  "2724": "ược",
+  "2725": "iề",
+  "2726": "▁được",
+  "2727": "▁nó",
+  "2728": "ững",
+  "2729": "▁cho",
+  "2730": "ấy",
+  "2731": "▁như",
+  "2732": "▁ngh",
+  "2733": "▁mà",
+  "2734": "▁tôi",
+  "2735": "ươ",
+  "2736": "ải",
+  "2737": "▁những",
+  "2738": "▁thì",
+  "2739": "ây",
+  "2740": "ao",
+  "2741": "▁đã",
+  "2742": "ần",
+  "2743": "▁cái",
+  "2744": "▁đó",
+  "2745": "▁đi",
+  "2746": "▁với",
+  "2747": "ướ",
+  "2748": "▁trong",
+  "2749": "▁các",
+  "2750": "iều",
+  "2751": "▁này",
+  "2752": "ũng",
+  "2753": "úng",
+  "2754": "ăm",
+  "2755": "ồi",
+  "2756": "ạn",
+  "2757": "▁anh",
+  "2758": "ư",
+  "2759": "ế",
+  "2760": "ạ",
+  "2761": "ộ",
+  "2762": "ờ",
+  "2763": "ả",
+  "2764": "ấ",
+  "2765": "ố",
+  "2766": "ớ",
+  "2767": "ệ",
+  "2768": "ề",
+  "2769": "ể",
+  "2770": "ơ",
+  "2771": "ủ",
+  "2772": "ậ",
+  "2773": "ợ",
+  "2774": "ầ",
+  "2775": "ị",
+  "2776": "ữ",
+  "2777": "ứ",
+  "2778": "ự",
+  "2779": "ọ",
+  "2780": "ồ",
+  "2781": "ở",
+  "2782": "ắ",
+  "2783": "ừ",
+  "2784": "ụ",
+  "2785": "ũ",
+  "2786": "ổ",
+  "2787": "ặ",
+  "2788": "ẽ",
+  "2789": "ằ",
+  "2790": "Đ",
+  "2791": "ỉ",
+  "2792": "ỏ",
+  "2793": "ử",
+  "2794": "ĩ",
+  "2795": "ỗ",
+  "2796": "ẫ",
+  "2797": "ẹ",
+  "2798": "ẩ",
+  "2799": "ễ",
+  "2800": "ẻ",
+  "2801": "ẳ",
+  "2802": "ỹ",
+  "2803": "ỡ",
+  "2804": "ỳ",
+  "2805": "ỷ",
+  "2806": "ẵ",
+  "2807": "Ở",
+  "2808": "ỵ",
+  "2809": "Ấ",
+  "2810": "Ý",
+  "2811": "Ừ",
+  "2812": "Ă",
+  "2813": "Ờ",
+  "2814": "Ả",
+  "2815": "Ồ",
+  "2816": "Ơ",
+  "2817": "Ư",
+  "2818": "Ứ",
+  "2819": "Ố",
+  "2820": "Ớ",
+  "2821": "Ủ",
+  "2822": "Ẩ",
+  "2823": "Ắ",
+  "2824": "Ổ",
+  "2825": "Ỷ",
+  "2826": "Ế",
+  "2827": "Ỳ",
+  "2828": "<blank>"
+}