From TensorFlow / TFLite

About TensorFlow

TensorFlow is a free and open-sourcearrow-up-right software libraryarrow-up-right for machine learningarrow-up-right and artificial intelligencearrow-up-right. It can be used across a range of tasks but has a particular focus on trainingarrow-up-right and inferencearrow-up-right of deep neural networksarrow-up-right.[4]arrow-up-right[5]arrow-up-right

TensorFlow was developed by the Google Brainarrow-up-right team for internal Googlearrow-up-right use in research and production.[6]arrow-up-right[7]arrow-up-right[8]arrow-up-right The initial version was released under the Apache License 2.0arrow-up-right in 2015.[1]arrow-up-right[9]arrow-up-rightGoogle released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019.[10]arrow-up-right

TensorFlow can be used in a wide variety of programming languages, including Pythonarrow-up-right, JavaScriptarrow-up-right, C++arrow-up-right, and Javaarrow-up-right.[11]arrow-up-right This flexibility lends itself to a range of applications in many different sectors.

Model deployment from TFLite

You can upload a TFLitearrow-up-right 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 toolsarrow-up-right, as illustrated in these examples: herearrow-up-right and herearrow-up-right.

Your TensorFlow model can be exported to ONNX and subsequently using cleaned and checked by the the sclblonnx package for an upload to the Nx AI cloud.

After obtaining a clean ONNX graph that adheres to our requirements, you can upload it to the Nx AI cloud for deployment.