I have a notebook here that has a image classifier skeleton

  
      github.com
  
  
    VishakBharadwaj94/CNN_starter/blob/main/CNN_Boilerplate.ipynb 2
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "source": [
    "# CNN outline for DL with CIFAR10\n",
    "\n",
    "![cifar10](https://miro.medium.com/max/709/1*LyV7_xga4jUHdx4_jHk1PQ.png)\n",
    "\n",
    "\n",
    "In this tutorial, we'll use the following techniques to achieve over 90% accuracy in less than 5 minutes:\n",
    "\n",
    "- Data normalization\n",
    "- Data augmentation\n",
    "- Residual connections\n",
    "- Batch normalization\n",


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I tried to fuse layers and quantize the model as in the video but got an error.
Deploying your ML Model with TorchServe

Are there any best practices for writing your model etc that overcome this problem?
Thanks!