# From TensorFlow / TFLite

## About TensorFlow

<figure><img src="/files/YlcpRNv0GFTeb6m2xIMG" alt="" width="500"><figcaption></figcaption></figure>

**TensorFlow** is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. TensorFlow was developed by the [Google Brain](https://en.wikipedia.org/wiki/Google_Brain) team for internal Google use in research and production.

TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java. This flexibility lends itself to a range of applications in many different sectors.

## Model deployment from TFLite

You can upload a [TFLite](https://www.tensorflow.org/lite) model directly, and the cloud will take care of exporting the model to ONNX.

## Model deployment from TensorFlow

Exporting from TensorFlow to ONNX is also possible using [the tf2onnx tools](https://github.com/onnx/tensorflow-onnx), as illustrated in these examples: [here](https://github.com/scailable/sclblonnx/blob/master/examples/example_04.py) and [here](https://onnxruntime.ai/docs/tutorials/tf-get-started.html#converting-a-model).

After obtaining a valid ONNX, you can upload it to the [Nx AI cloud for deployment](/nx-ai-manager-v6.1.2/nx-ai-cloud-ui/upload-your-model.md).


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