From f9c5174f0e477ea6f619497f8d3b352d05be3aab Mon Sep 17 00:00:00 2001
From: Paige Bailey <webpaige@google.com>
Date: Fri, 19 Jul 2024 10:02:43 -0700
Subject: [PATCH] Added "Open in Colab" button to each notebook.

---
 colabs/fine_tuning_tutorial.ipynb | 48 +++++++++++++++++--------------
 colabs/gsm8k_eval.ipynb           | 29 ++++++++++++-------
 colabs/sampling_tutorial.ipynb    | 25 ++++++++++------
 3 files changed, 60 insertions(+), 42 deletions(-)

diff --git a/colabs/fine_tuning_tutorial.ipynb b/colabs/fine_tuning_tutorial.ipynb
index 421c8e6..c775002 100644
--- a/colabs/fine_tuning_tutorial.ipynb
+++ b/colabs/fine_tuning_tutorial.ipynb
@@ -31,6 +31,10 @@
    "source": [
     "# Fine-tuning the 2B Gemma model with flax\n",
     "\n",
+    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/google-deepmind/gemma/blob/main/colabs/fine_tuning_tutorial.ipynb\">\n",
+    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
+    "</a>\n",
+    "\n",
     "In this tutorial you will learn how to fine-tune the 2B Gemma model for a simple translation task. To run this colab, you will need to use a TPU v4 runtime."
    ]
   },
@@ -45,7 +49,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "XpSw-_4EEcoY"
    },
@@ -75,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "8q5seOhcUBhx"
    },
@@ -102,7 +106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "9PEefz8wEcoY"
    },
@@ -119,7 +123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "yWaP_LPoEcoY"
    },
@@ -167,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "pg8SfQH0EcoY"
@@ -208,7 +212,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "TpyG5YW1EcoY"
@@ -236,7 +240,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "L9cjK0uxEcoY"
@@ -308,7 +312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "xEA-97ioEcoY"
@@ -351,7 +355,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "XwFFs2mDEcoY"
@@ -495,7 +499,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "bYeduOaNEcoZ"
@@ -529,7 +533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "VDlfziQVEcoZ"
@@ -563,7 +567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "jWr6Sea_EcoZ"
@@ -579,7 +583,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "S6937NTjEcoZ"
@@ -606,7 +610,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "LbJa4S5WEcoZ"
@@ -637,7 +641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "iEcV0XEEEcoZ"
@@ -707,7 +711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "cbWfdHf0EcoZ"
@@ -735,7 +739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "cPSfp7ZUEcoZ"
@@ -790,7 +794,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "yU4oR92YEcoa"
@@ -823,7 +827,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "xT4bAqNLEcoa"
@@ -921,7 +925,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "7SL2VAmVEcoa"
@@ -955,7 +959,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "dQ1oCF10Ecod"
@@ -980,7 +984,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "S5F3fk22Ecod"
diff --git a/colabs/gsm8k_eval.ipynb b/colabs/gsm8k_eval.ipynb
index 304c934..13e7cad 100644
--- a/colabs/gsm8k_eval.ipynb
+++ b/colabs/gsm8k_eval.ipynb
@@ -25,6 +25,10 @@
    "source": [
     "# GSM8K evaluation using Gemma\n",
     "\n",
+    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/google-deepmind/gemma/blob/main/colabs/gsm8k_eval.ipynb\">\n",
+    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
+    "</a>\n",
+    "\n",
     "The [GSM8K dataset](https://arxiv.org/pdf/2110.14168.pdf) presents a good evaluation challenge for small models for several reasons:\n",
     "\n",
     "1. **Conceptual Simplicity:** While the problems in GSM8K require multi-step reasoning, they primarily involve elementary mathematical concepts and basic arithmetic operations. This makes the dataset accessible to smaller models that may not have the capacity to handle complex mathematical reasoning.\n",
@@ -51,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "pIF7Tr8yEXiq"
    },
@@ -80,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "qai-J2Dgaac0"
    },
@@ -107,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "-uHzK733EXiq"
    },
@@ -124,7 +128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "udFgOLxJEXiq"
    },
@@ -151,7 +155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "E47hYa8dEXiq"
@@ -164,7 +168,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "ReheKSODEXiq"
@@ -209,7 +213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "cXoCKMi9EXir"
@@ -331,7 +335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "7s15QMbbEXir"
@@ -353,7 +357,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "_n0KePI2EXir"
@@ -375,7 +379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "51WOHSzVEXir"
@@ -407,7 +411,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "iHxQeQ4hEXir"
@@ -463,6 +467,9 @@
  "metadata": {
   "colab": {
    "private_outputs": true
+  },
+  "language_info": {
+   "name": "python"
   }
  },
  "nbformat": 4,
diff --git a/colabs/sampling_tutorial.ipynb b/colabs/sampling_tutorial.ipynb
index 9563adf..487e12f 100644
--- a/colabs/sampling_tutorial.ipynb
+++ b/colabs/sampling_tutorial.ipynb
@@ -25,6 +25,10 @@
    "source": [
     "# Getting Started with Gemma Sampling: A Step-by-Step Guide\n",
     "\n",
+    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/google-deepmind/gemma/blob/main/colabs/sampling_tutorial.ipynb\">\n",
+    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
+    "</a>\n",
+    "\n",
     "You will find in this colab a detailed tutorial explaining how to load a Gemma checkpoint and sample from it.\n",
     "\n"
    ]
@@ -40,7 +44,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "iq2ebV_6YNiU"
    },
@@ -69,7 +73,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "likVQiEEYS5X"
    },
@@ -96,7 +100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "id": "O-sxcasvESaM"
    },
@@ -113,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "-jpTUa1YESaM"
@@ -140,7 +144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "57nMYQ4HESaN"
@@ -162,7 +166,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "khXrjEF0ESaN"
@@ -184,7 +188,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "7InOzQtcESaN"
@@ -209,7 +213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "bdstASGrESaN"
@@ -235,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "qA0BhNQvESaN"
@@ -271,6 +275,9 @@
  "metadata": {
   "colab": {
    "private_outputs": true
+  },
+  "language_info": {
+   "name": "python"
   }
  },
  "nbformat": 4,