Update triton.md parameter type (#1985)

docs/extend/modular-resources/examples/triton.md

@@ -128,7 +128,7 @@ The following attributes are available for the MLModel service `viam:mlmodelserv
 | `model_version` | int | Optional | The version of the model to be loaded. If not specified, the module will use the newest version of the model named by model_name. <br> Default: `-1` (newest) |
 | `preferred_input_memory_type` | string | Optional | One of `cpu`, `cpu-pinned`, or `gpu`. This controlls the type of memory that will be allocated by the module for input tensors. If not specified, this will default to `cpu` if no CUDA-capable devices are detected at runtime, or to `gpu` if CUDA-capable devices are found.|
 | `preferred_input_memory_type_id` | int | Optional | CUDA identifier on which to allocate gpu or cpu-pinned input tensors. You probably don't need to change this unless you have multiple GPUs. <br> Default: `0` (first device) |
-| `tensor_name_remappings` | string | Optional | Provides two dictionaries under the `input` and `output` keys that rename the models' tensors. Other Viam services, like the [vision service](/services/vision/) may expect to work with tensors with particular names. Use this map to rename the tensors from the loaded model as needed to meet those requirements. <br> Default: `{}` |
+| `tensor_name_remappings` | obj | Optional | Provides two dictionaries under the `input` and `output` keys that rename the models' tensors. Other Viam services, like the [vision service](/services/vision/) may expect to work with tensors with particular names. Use this map to rename the tensors from the loaded model as needed to meet those requirements. <br> Default: `{}` |
 
 An example minimal configuration would look like this, within your robot's `"services"` array: