diff --git a/unit3/unit3.ipynb b/unit3/unit3.ipynb
index 5ea14bf..5999413 100644
--- a/unit3/unit3.ipynb
+++ b/unit3/unit3.ipynb
@@ -3,8 +3,8 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "colab_type": "text",
-        "id": "view-in-github"
+        "id": "view-in-github",
+        "colab_type": "text"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/unit3/unit3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -279,7 +279,9 @@
         "- We use the Atari Wrapper that preprocess the input (Frame reduction ,grayscale, stack 4 frames)\n",
         "- We use `CnnPolicy`, since we use Convolutional layers to process the frames\n",
         "- We train it for 10 million `n_timesteps` \n",
-        "- Memory (Experience Replay) size is 100000"
+        "- Memory (Experience Replay) size is 100000\n",
+        "\n",
+        "💡 My advice is to **reduce the training timesteps to 1M,** if you want to train for 10M timesteps, you should run on your local machine (to avoid Colab timeout) to do that just click on: `File>Download`"
       ]
     },
     {
@@ -712,12 +714,11 @@
   ],
   "metadata": {
     "colab": {
-      "authorship_tag": "ABX9TyPwiHKn+ccCskGi3ZMw9yH2",
       "collapsed_sections": [],
-      "include_colab_link": true,
       "name": "Copie de Unit 3: Deep Q-Learning with Space Invaders.ipynb",
       "private_outputs": true,
-      "provenance": []
+      "provenance": [],
+      "include_colab_link": true
     },
     "kernelspec": {
       "display_name": "Python 3",
@@ -729,4 +730,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}
\ No newline at end of file