# Run a model Source: [https://docs.qualcomm.com/doc/80-70014-54/topic/execute-a-model.html](https://docs.qualcomm.com/doc/80-70014-54/topic/execute-a-model.html) To run inference, invoke a delegate using the `Invoke()` API. Before invoking this API, create the appropriate input and output buffers and provide them to the interpreter. After inference is complete, you can parse the output from the interpreter output buffers to get inference results. An example of the `Invoke()` API executing a model using a delegate is as follows: // Run Inference interpreter->Invoke() Copy to clipboard After inference is completed, output tensors from the TensorFlow Lite `Invoke()` API are present in the output buffers of the interpreter. To perform further postprocessing on these outputs, you can parse them from the interpreter. For an end-to-end example, see the label\_image example in the [TensorFlow GitHub repository](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/examples/label_image). For more information, see [TensorFlow Lite Guide](https://www.tensorflow.org/lite/guide). **Parent Topic:** [Run inference](https://docs.qualcomm.com/doc/80-70014-54/topic/run-inference.html) Last Published: Jul 12, 2024 [Previous Topic Prepare input/output buffers](https://docs.qualcomm.com/bundle/publicresource/80-70014-54/topics/prepare-input-output-buffers.md) [Next Topic Develop a custom application to run the TensorFlow Lite model](https://docs.qualcomm.com/bundle/publicresource/80-70014-54/topics/develop-a-custom-application-to-run-the-tensorflow-lite-model.md)