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Big Transfer Image Classification Model Quantization with NNCF in OpenVINO™

This tutorial demonstrates how to apply 'INT8' quantization to the Big Transfer Image Classification model. Here we demonstrate fine-tuning the model, OpenVINO optimization and followed by INT8 quantization processing with NNCF.

Notebook Contents

This tutorial consists of the following steps:

  • Prepare Dataset.
  • Plotting data samples.
  • Model fine-tuning.
  • Perform model optimization (IR) step.
  • Compute model accuracy of the TF model.
  • Compute model accuracy of the optimized model.
  • Run nncf.Quantize for getting an Optimized model.
  • Compute model accuracy of the quantized model.
  • Compare model accuracy of the optimized and quantized models.
  • Compare inference results on one picture

Installation Instructions

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