[Nano] Openvino quantization notebooks with nano (intel-analytics#5491)

* notebook with nano * load with nano * modify readme * clear all outputs and enable benchmark_app * fix typo
ForJadeForest · Sep 20, 2022 · 24176ea · 24176ea
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diff --git a/python/nano/notebooks/pytorch/openvino/quantization-simplified-mode/README.md b/python/nano/notebooks/pytorch/openvino/quantization-simplified-mode/README.md
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 # Simplified Post-Training Quantization of Image Classification Models with OpenVINO™ 
+This tutorial was adapted from https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/114-quantization-simplified-mode. Here, we use OpenVINO APIs provided by BigDL Nano instead to simplify the original tutorial.
 
 This tutorial demostrates how to perform INT8 quantization with an image classification model using the [Post-Training Optimization
 Tool Simplified Mode](https://docs.openvino.ai/latest/pot_docs_simplified_mode.html) (part of [OpenVINO](https://docs.openvino.ai/)). We use [ResNet20](https://github.com/chenyaofo/pytorch-cifar-models/blob/master/pytorch_cifar_models/resnet.py) model and [Cifar10](http://pytorch.org/vision/main/generated/torchvision.datasets.CIFAR10.html) dataset.