fix: client ipynb

client.ipynb

@@ -69,7 +69,9 @@
    "source": [
     "Using client is super easy. The following steps are best run in Jupyter notebook or [Google Colab](https://colab.research.google.com/github/jina-ai/dalle-flow/blob/main/client.ipynb).  \n",
     "\n",
-    "The only dependency you will need are [DocArray](https://github.com/jina-ai/docarray) and [Jina](https://github.com/jina-ai/jina), as DocArray is already included in Jina you only need to install `jina`\""
+    "The only dependency you will need are [DocArray](https://github.com/jina-ai/docarray) and [Jina](https://github.com/jina-ai/jina), as DocArray is already included in Jina you only need to install `jina`.\n",
+    "\n",
+    "> On Google Colab, you will be asked to restart the kernel. Go ahead and restart."
    ]
   },
   {
@@ -322,20 +324,26 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a1c5b2bb",
+   "cell_type": "markdown",
+   "id": "e910e8aa",
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
-   "outputs": [],
    "source": [
     "> 💁‍♂️ On Google colab this image may render exactly the same size as before. But it is in 1024x1024 already. Right click on the image and copy/save it. You will see.\n",
     "\n",
     "That's it! It is _the one_. If not satisfied, please repeat the procedure. Btw, DocArray is a powerful and easy-to-use data structure for unstructured data. It is super productive for data scientists who work in cross-/multi-modal domain. To learn more about DocArray, [please check out the docs](https://docarray.jina.ai)."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "50f267e1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {