edit aws_marketplace/using-open-source-model-packages/pytorch-ic-mode…

…l/using-image-classification-models.ipynb

aws_marketplace/using-open-source-model-packages/pytorch-ic-model/using-image-classification-models.ipynb

@@ -10,7 +10,7 @@
     "\n",
     "This notebook is compatible only with those image classification model packages which this notebook is linked to.\n",
     "\n",
-    "#### Pre-requisites:\n",
+    "## Pre-requisites:\n",
     "1. **Note**: This notebook contains elements which render correctly in Jupyter interface. Open this notebook from an Amazon SageMaker Notebook Instance or Amazon SageMaker Studio.\n",
     "1. Ensure that IAM role used has **AmazonSageMakerFullAccess**\n",
     "1. To deploy this ML model successfully, ensure that:\n",
@@ -20,7 +20,7 @@
     "        1. **aws-marketplace:Subscribe**  \n",
     "    2. or your AWS account has a subscription to this image classification model. If so, skip step: [Subscribe to the model package](#1.-Subscribe-to-the-model-package)\n",
     "\n",
-    "#### Contents:\n",
+    "## Contents\n",
     "1. [Subscribe to the model package](#1.-Subscribe-to-the-model-package)\n",
     "2. [Create an endpoint and perform real-time inference](#2.-Create-an-endpoint-and-perform-real-time-inference)\n",
     "   1. [Create an endpoint](#A.-Create-an-endpoint)\n",
@@ -34,7 +34,7 @@
     "    2. [Unsubscribe to the listing (optional)](#B.-Unsubscribe-to-the-listing-(optional))\n",
     "    \n",
     "\n",
-    "#### Usage instructions\n",
+    "## Usage instructions\n",
     "You can run this notebook one cell at a time (By using Shift+Enter for running a cell).\n",
     "\n",
     "**Note** - This notebook requires you to follow instructions and specify values for parameters, as instructed."
@@ -44,7 +44,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 1. Subscribe to the model package"
+    "## 1. Subscribe to the model package"
    ]
   },
   {
@@ -107,7 +107,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 2. Create an endpoint and perform real-time inference"
+    "## 2. Create an endpoint and perform real-time inference"
    ]
   },
   {
@@ -151,7 +151,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### A. Create an endpoint"
+    "### A. Create an endpoint"
    ]
   },
   {
@@ -180,7 +180,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### B. Prepare input file for performing real-time inference\n",
+    "### B. Prepare input file for performing real-time inference\n",
     "In this step, we will download class_id_to_label_mapping from S3 bucket. The mapping files has been downloaded from [TensorFlow](https://storage.googleapis.com/download.tensorflow.org/data/ImageNetLabels.txt). [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0)."
    ]
   },
@@ -240,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### C. Query endpoint that you have created with the opened images"
+    "### C. Query endpoint that you have created with the opened images"
    ]
   },
   {
@@ -286,7 +286,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### D. Delete the endpoint"
+    "### D. Delete the endpoint"
    ]
   },
   {
@@ -310,7 +310,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 3. Perform batch inference"
+    "## 3. Perform batch inference"
    ]
   },
   {
@@ -386,14 +386,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 4. Clean-up"
+    "## 4. Clean-up"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### A. Delete the model"
+    "### A. Delete the model"
    ]
   },
   {
@@ -409,7 +409,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### B. Unsubscribe to the listing (optional)"
+    "### B. Unsubscribe to the listing (optional)"
    ]
   },
   {