# How do I run my model on an embedded device?

After [training](../guides/model_training.md) a model, `.tflite` model
file is generated (See the FAQ [Where is my trained model?](./where_is_my_trained_model.md) for more details).

This file is programmed to the embedded device which is then loaded
and executed by the [Tensorflow-Lite Micro](https://github.com/tensorflow/tflite-micro) (TFLM) interpreter.

The `.tflite` can be thought of as a binary blob. It simply needs to be converted to
a `uint8_t` C array which can then be directly given to the TFLM interpreter.

There are several different ways to deploy your model to an embedded device, including:


## Simplicity Studio
  
From your [Simplicity Studio](../cpp_development/simplicity_studio.md) project, replace the default model 
by renaming your `.tflite` file to `1_<your model named>.tflite` and copy it into the `config/tflite` folder 
of the Simplicity Studio project. (Simplicity Studio sorts the models alphabetically in ascending order, adding `1_` 
forces the model to come first). After a new .tflite file is added to the  project Simplicity Studio will automatically use the 
[flatbuffer converter tool](https://docs.silabs.com/gecko-platform/latest/machine-learning/tensorflow/flatbuffer-conversion)
to convert a .tflite file into a C file which is added to the project.

Refer to the online [documentation](https://docs.silabs.com/gecko-platform/latest/machine-learning/tensorflow/guide-replace-model#updating-or-replacing-the--tflite-file-in-a-project) for more details.

## CMake
 
The MLTK features several [example applications](../cpp_development/examples/index.md).
These applications can be built with [VS Code](../cpp_development/vscode.md) or the CMake [command line](../cpp_development/command_line.md).

Supported applications such as:  
- [Model Profiler](../cpp_development/examples/model_profiler.md)
- [Audio Classifier](../cpp_development/examples/audio_classifier.md)

Allow for defining [build options](../cpp_development/build_options.md) that specify the path to the `.tflite` model file.

e.g., to `<mltk repo root>/user_options.cmake`, add:

```
mltk_set(MODEL_PROFILER_MODEL "~/workspace/my_model.tflite")
mltk_set(AUDIO_CLASSIFIER_MODEL "~/workspace/my_model.tflite")
```

## Command line
  
The MLTK features several [example applications](../cpp_development/examples/index.md).

Supported applications such as:  
- [Model Profiler](../cpp_development/examples/model_profiler.md)
- [Audio Classifier](../cpp_development/examples/audio_classifier.md)

Allow for overriding the default `.tflite` model built into the application.
When the application starts, it checks the end of flash memory for a `.tflite` model file. If found, the model
at the end of flash is used instead of the default model.

To write the model to flash, use the command:

```shell
mltk update_params <model name> --device
```

Refer to the command's help for more details:

```shell
mltk update_params --help
```