Update open in colab badge

example_colabs/quick_start.ipynb

@@ -1,30 +1,14 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "colab": {
-      "provenance": [],
-      "collapsed_sections": [
-        "vCM_sxQsg2nj",
-        "nSHa2LHCg7Gz",
-        "tNzvaoFHhBJR",
-        "Q3aMYkE6HMPM"
-      ],
-      "private_outputs": true
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
   "cells": [
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "Earrbj1HNaVk"
+      },
       "source": [
-        "# Google AI Edge Model Explorer [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-ai-edge/model-explorer/blob/main/example_colabs/quick_start.ipynb)\n",
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-ai-edge/model-explorer/blob/main/example_colabs/quick_start.ipynb)\n",
+        "\n",
+        "# Google AI Edge Model Explorer\n",
         "A visualization tool that lets you analyze ML models and graphs, accelerating deployment to on-device targets. [Learn more](https://ai.google.dev/edge/model-explorer).\n",
         "\n",
         "**Key Features**\n",
@@ -37,19 +21,16 @@
         "Follow the [installation instructions](https://github.com/google-ai-edge/model-explorer/wiki/5.-Run-in-Colab-Notebook) to add it to your own Colab.\n",
         "\n",
         "Want to run Model Explorer locally? [Get Started here](https://github.com/google-ai-edge/model-explorer/wiki/1.-Installation)"
-      ],
-      "metadata": {
-        "id": "Earrbj1HNaVk"
-      }
+      ]
     },
     {
       "cell_type": "markdown",
-      "source": [
-        "# Download a copy of the EfficientDet TFLite model"
-      ],
       "metadata": {
         "id": "vCM_sxQsg2nj"
-      }
+      },
+      "source": [
+        "# Download a copy of the EfficientDet TFLite model"
+      ]
     },
     {
       "cell_type": "code",
@@ -72,71 +53,92 @@
     },
     {
       "cell_type": "markdown",
-      "source": [
-        "# Install Model Explorer using pip"
-      ],
       "metadata": {
         "id": "nSHa2LHCg7Gz"
-      }
+      },
+      "source": [
+        "# Install Model Explorer using pip"
+      ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "!pip install --no-deps model-explorer-adapter ai-edge-model-explorer"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "XqnjhEVqkSvU"
       },
-      "execution_count": null,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "!pip install --no-deps model-explorer-adapter ai-edge-model-explorer"
+      ]
     },
     {
       "cell_type": "markdown",
-      "source": [
-        "# Visualize the downloaded EfficientDet model"
-      ],
       "metadata": {
         "id": "tNzvaoFHhBJR"
-      }
+      },
+      "source": [
+        "# Visualize the downloaded EfficientDet model"
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "_qycf3tbmP_S"
+      },
+      "outputs": [],
       "source": [
         "import model_explorer\n",
         "\n",
         "model_explorer.visualize(model_path)"
-      ],
-      "metadata": {
-        "id": "_qycf3tbmP_S"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "Q3aMYkE6HMPM"
+      },
       "source": [
         "# Visualize a PyTorch model\n",
         "\n"
-      ],
-      "metadata": {
-        "id": "Q3aMYkE6HMPM"
-      }
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "sZJkEgdsHSH9"
+      },
+      "outputs": [],
       "source": [
         "# Get mobilnet v2 pytorch model as an example.\n",
         "model = torchvision.models.mobilenet_v2().eval()\n",
         "inputs = (torch.rand([1, 3, 224, 224]),)\n",
         "\n",
         "# Visualize\n",
         "model_explorer.visualize_pytorch('mobilenet', model, inputs)"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "collapsed_sections": [
+        "vCM_sxQsg2nj",
+        "nSHa2LHCg7Gz",
+        "tNzvaoFHhBJR",
+        "Q3aMYkE6HMPM"
       ],
-      "metadata": {
-        "id": "sZJkEgdsHSH9"
-      },
-      "execution_count": null,
-      "outputs": []
+      "private_outputs": true,
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
     }
-  ]
-}
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}