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Optimizing TensorFlow models with Neural Network Compression Framework of OpenVINO™ by 8-bit quantization.

This tutorial demonstrates how to use NNCF 8-bit quantization to optimize the TensorFlow model for inference with OpenVINO Toolkit. For more advanced usage, refer to these examples.

To speed up download and training, use a ResNet-18 model with the Imagenette dataset. Imagenette is a subset of 10 easily classified classes from the ImageNet dataset.

Notebook Contents

This tutorial consists of the following steps:

  • Fine-tuning of FP32 model
  • Transforming the original FP32 model to INT8
  • Using fine-tuning to restore the accuracy.
  • Exporting optimized and original models to Frozen Graph and then to OpenVINO
  • Measuring and comparing the performance of the models.

Installation Instructions

If you have not installed all required dependencies, follow the Installation Guide.