onnx and tensorflow-onnx
The ONNX specification defines the interoperability standard, while tensorflow-onnx is a converter tool that enables TensorFlow models to be deployed using that standard—making them complementary tools used together in a conversion workflow.
About onnx
onnx/onnx
Open standard for machine learning interoperability
This project offers an open-source format for AI models, helping AI developers use different machine learning tools interchangeably. It takes an AI model trained in one framework and converts it into a standardized format, allowing it to be used (especially for scoring/inferencing) in another framework or hardware. AI developers who build and deploy machine learning models are the primary users.
About tensorflow-onnx
onnx/tensorflow-onnx
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
This tool helps machine learning engineers and data scientists convert their trained models built with TensorFlow, Keras, TensorFlow.js, or TFLite into the ONNX format. You provide your existing model file, and it outputs a universal ONNX model, which can then be deployed across various hardware and runtimes. It's for anyone needing to standardize or port their TensorFlow ecosystem models for broader compatibility and deployment flexibility.
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