fix overview

tutorials/notebooks/example_quick_start_torchvision.ipynb

@@ -10,19 +10,24 @@
       "source": [
         "# Quick Start\n",
         "\n",
-        "[Run this tutorial in Google Colab](https://colab.research.google.com/github/sony/model_optimization/blob/quickstart-table/tutorials/notebooks/example_quick_start_torchvision.ipynb)\n",
-        "\n",
-        "Overview\n",
+        "[Run this tutorial in Google Colab](https://colab.research.google.com/github/sony/model_optimization/blob/quickstart-table/tutorials/notebooks/example_quick_start_torchvision.ipynb)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "9bc664bf",
+      "metadata": {},
+      "source": [
+        "## Overview\n",
         "This tutorial shows how to use \"quick-start\" with a pre-trained model from the torchvision library.\n",
         "\n",
         "The following steps will be covered:\n",
         "\n",
-        "Steps:\n",
         "* **Setup the environment**: install MCT and add tutorials to PYTHONPATH\n",
         "* **Download and organize the imagenet dataset**\n",
         "* **Run quick_start on your model**\n",
         "\n",
-        "**Note**: The following code should be run on a GPU."
+        "**Note**: The following code will run faster on a GPU."
       ]
     },
     {
@@ -46,7 +51,8 @@
         "id": "eda6ab0d8f0b6b56"
       },
       "source": [
-        "In order to convert the PyTorch model, you'll need to use the conversion code in the [MCT tutorials folder](https://github.com/sony/model_optimization/tree/main/tutorials), so we'll clone the MCT repository to a local folder and only use that code. The installed MCT package will be used for quantization.\n",
+        "In order to use quick-start you'll need the [MCT tutorial folder](https://github.com/sony/model_optimization/tree/main/tutorials), so we'll clone the MCT repository to a local folder and use that code.\n",
+        "\n",
         "  **It's important to note that we use the most up-to-date MCT code available.**"
       ]
     },
@@ -64,20 +70,20 @@
       "outputs": [],
       "source": [
         "!git clone https://github.com/sony/model_optimization.git local_mct\n",
-        "!pip install -r /content/local_mct/requirements.txt"
+        "!pip install -r ./local_mct/requirements.txt"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 2,
+      "execution_count": null,
       "id": "PfJ3_AyieBL0",
       "metadata": {
         "id": "PfJ3_AyieBL0"
       },
       "outputs": [],
       "source": [
         "import os\n",
-        "os.environ['PYTHONPATH'] = '/content/local_mct/'"
+        "os.environ['PYTHONPATH'] = './local_mct/'"
       ]
     },
     {
@@ -92,7 +98,7 @@
         "\n",
         "Use torchvision.datasets.ImageNet to create the dataset in the correct structure.\n",
         "\n",
-        "**Note**: We use validation for time convinience since the training split is too big. To measure accurate validation results, the validation samples should only be used for testing."
+        "**Note**: We use validation for time convinience since the training split is too big. Typically, the validation samples should only be used for testing."
       ]
     },
     {
@@ -125,7 +131,7 @@
       "outputs": [],
       "source": [
         "import torchvision\n",
-        "ds = torchvision.datasets.ImageNet(root='/content/imagenet', split='val')"
+        "ds = torchvision.datasets.ImageNet(root='./imagenet', split='val')"
       ]
     },
     {
@@ -135,7 +141,11 @@
         "id": "gY2UsnzOfjtk"
       },
       "source": [
-        "## Run Quick Start script on our model of choice"
+        "## Run Quick Start script on our model of choice\n",
+        "\n",
+        "Here we set the model name, model library, validation dataset path, and representative datasets path.\n",
+        " \n",
+        "The remaining arguments are left with their default settings. Please verify that the dataset paths are configured correctly."
       ]
     },
     {
@@ -151,7 +161,7 @@
       },
       "outputs": [],
       "source": [
-        "!python /content/local_mct/tutorials/quick_start/main.py --model_name mobilenet_v2 --model_library torchvision --validation_dataset_folder /content/imagenet/val --representative_dataset_folder /content/imagenet/val"
+        "!python ./local_mct/tutorials/quick_start/main.py --model_name mobilenet_v2 --model_library torchvision --validation_dataset_folder ./imagenet/val --representative_dataset_folder ./imagenet/val"
       ]
     },
     {