Add example notebook for AutoSummarization (#19)

* Create 03_TextSummarization.ipynb

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examples/nbs/03_TextSummarization.ipynb

@@ -0,0 +1,90 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "xYgiH2TkkX7x"
+   },
+   "outputs": [],
+   "source": [
+    "!pip install lightning-flash\n",
+    "!pip install git+https://github.com/gradsflow/gradsflow@main"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "2_posF7Rj8sH"
+   },
+   "outputs": [],
+   "source": [
+    "from flash.core.data.utils import download_data\n",
+    "from flash.text import SummarizationData, SummarizationTask\n",
+    "\n",
+    "# 1. Download the data\n",
+    "download_data(\"https://pl-flash-data.s3.amazonaws.com/xsum.zip\", \"data/\")\n",
+    "\n",
+    "# 2. Load the data\n",
+    "datamodule = SummarizationData.from_csv(\n",
+    "    \"input\",\n",
+    "    \"target\",\n",
+    "    train_file=\"data/xsum/train.csv\",\n",
+    "    val_file=\"data/xsum/valid.csv\",\n",
+    "    test_file=\"data/xsum/test.csv\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YCYFfKhDkVVK"
+   },
+   "outputs": [],
+   "source": [
+    "from gradsflow.autoclassifier import AutoSummarization\n",
+    "\n",
+    "suggested_conf = dict(\n",
+    "    optimizers=[\"adam\"],\n",
+    "    lr=(5e-4, 1e-3),\n",
+    ")\n",
+    "\n",
+    "model = AutoSummarization(datamodule,\n",
+    "                           suggested_backbones=\"sshleifer/distilbart-cnn-12-6\",\n",
+    "                           suggested_conf=suggested_conf,\n",
+    "                           max_epochs=1,\n",
+    "                           optimization_metric=\"train_loss\",\n",
+    "                           timeout=5)\n",
+    "\n",
+    "print(\"AutoSummarization initialised!\")\n",
+    "model.hp_tune()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "w_KVlJxYpTVy"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "03-TextSummarization.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}