diff --git "a/Reader.ipynb" "b/Reader.ipynb"
new file mode 100644--- /dev/null
+++ "b/Reader.ipynb"
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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Ifq5xlTrsc7B",
+        "outputId": "48823469-9e7f-47e2-979c-02fff9911e79"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Collecting datasets==1.17.0\n",
+            "  Downloading datasets-1.17.0-py3-none-any.whl (306 kB)\n",
+            "\u001b[K     |████████████████████████████████| 306 kB 5.1 MB/s \n",
+            "\u001b[?25hCollecting transformers==4.15.0\n",
+            "  Downloading transformers-4.15.0-py3-none-any.whl (3.4 MB)\n",
+            "\u001b[K     |████████████████████████████████| 3.4 MB 20.1 MB/s \n",
+            "\u001b[?25hCollecting tokenizers\n",
+            "  Downloading tokenizers-0.11.4-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.8 MB)\n",
+            "\u001b[K     |████████████████████████████████| 6.8 MB 40.5 MB/s \n",
+            "\u001b[?25hCollecting xxhash\n",
+            "  Downloading xxhash-2.0.2-cp37-cp37m-manylinux2010_x86_64.whl (243 kB)\n",
+            "\u001b[K     |████████████████████████████████| 243 kB 54.9 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (4.62.3)\n",
+            "Requirement already satisfied: dill in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (0.3.4)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (1.3.5)\n",
+            "Collecting huggingface-hub<1.0.0,>=0.1.0\n",
+            "  Downloading huggingface_hub-0.4.0-py3-none-any.whl (67 kB)\n",
+            "\u001b[K     |████████████████████████████████| 67 kB 4.7 MB/s \n",
+            "\u001b[?25hCollecting aiohttp\n",
+            "  Downloading aiohttp-3.8.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB)\n",
+            "\u001b[K     |████████████████████████████████| 1.1 MB 51.2 MB/s \n",
+            "\u001b[?25hCollecting fsspec[http]>=2021.05.0\n",
+            "  Downloading fsspec-2022.1.0-py3-none-any.whl (133 kB)\n",
+            "\u001b[K     |████████████████████████████████| 133 kB 52.3 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: pyarrow!=4.0.0,>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (6.0.1)\n",
+            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (2.23.0)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (21.3)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (1.19.5)\n",
+            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (4.10.1)\n",
+            "Requirement already satisfied: multiprocess in /usr/local/lib/python3.7/dist-packages (from datasets==1.17.0) (0.70.12.2)\n",
+            "Collecting tokenizers\n",
+            "  Downloading tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)\n",
+            "\u001b[K     |████████████████████████████████| 3.3 MB 17.8 MB/s \n",
+            "\u001b[?25hCollecting sacremoses\n",
+            "  Downloading sacremoses-0.0.47-py2.py3-none-any.whl (895 kB)\n",
+            "\u001b[K     |████████████████████████████████| 895 kB 48.8 MB/s \n",
+            "\u001b[?25hCollecting pyyaml>=5.1\n",
+            "  Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\n",
+            "\u001b[K     |████████████████████████████████| 596 kB 44.0 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.15.0) (2019.12.20)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers==4.15.0) (3.4.2)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets==1.17.0) (3.10.0.2)\n",
+            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->datasets==1.17.0) (3.0.7)\n",
+            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets==1.17.0) (2.10)\n",
+            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets==1.17.0) (1.24.3)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets==1.17.0) (2021.10.8)\n",
+            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets==1.17.0) (3.0.4)\n",
+            "Collecting multidict<7.0,>=4.5\n",
+            "  Downloading multidict-6.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (94 kB)\n",
+            "\u001b[K     |████████████████████████████████| 94 kB 3.2 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==1.17.0) (2.0.11)\n",
+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==1.17.0) (21.4.0)\n",
+            "Collecting asynctest==0.13.0\n",
+            "  Downloading asynctest-0.13.0-py3-none-any.whl (26 kB)\n",
+            "Collecting aiosignal>=1.1.2\n",
+            "  Downloading aiosignal-1.2.0-py3-none-any.whl (8.2 kB)\n",
+            "Collecting async-timeout<5.0,>=4.0.0a3\n",
+            "  Downloading async_timeout-4.0.2-py3-none-any.whl (5.8 kB)\n",
+            "Collecting frozenlist>=1.1.1\n",
+            "  Downloading frozenlist-1.3.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (144 kB)\n",
+            "\u001b[K     |████████████████████████████████| 144 kB 53.4 MB/s \n",
+            "\u001b[?25hCollecting yarl<2.0,>=1.0\n",
+            "  Downloading yarl-1.7.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (271 kB)\n",
+            "\u001b[K     |████████████████████████████████| 271 kB 51.7 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->datasets==1.17.0) (3.7.0)\n",
+            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets==1.17.0) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets==1.17.0) (2018.9)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->datasets==1.17.0) (1.15.0)\n",
+            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.15.0) (7.1.2)\n",
+            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.15.0) (1.1.0)\n",
+            "Installing collected packages: multidict, frozenlist, yarl, asynctest, async-timeout, aiosignal, pyyaml, fsspec, aiohttp, xxhash, tokenizers, sacremoses, huggingface-hub, transformers, datasets\n",
+            "  Attempting uninstall: pyyaml\n",
+            "    Found existing installation: PyYAML 3.13\n",
+            "    Uninstalling PyYAML-3.13:\n",
+            "      Successfully uninstalled PyYAML-3.13\n",
+            "Successfully installed aiohttp-3.8.1 aiosignal-1.2.0 async-timeout-4.0.2 asynctest-0.13.0 datasets-1.17.0 frozenlist-1.3.0 fsspec-2022.1.0 huggingface-hub-0.4.0 multidict-6.0.2 pyyaml-6.0 sacremoses-0.0.47 tokenizers-0.10.3 transformers-4.15.0 xxhash-2.0.2 yarl-1.7.2\n"
+          ]
+        }
+      ],
+      "source": [
+        "! pip  install datasets==1.17.0 transformers==4.15.0 tokenizers"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ODMsWgERsuxG",
+        "outputId": "87058980-d31d-4e05-c72e-d22aea47fb54"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[1m\u001b[31mWARNING! `transformers-cli login` is deprecated and will be removed in v5. Please use `huggingface-cli login` instead.\u001b[0m\n",
+            "\n",
+            "        _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
+            "        _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
+            "        _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
+            "        _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
+            "        _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
+            "\n",
+            "        \n",
+            "Username: Vasanth\n",
+            "Password: \n",
+            "ERROR:root:HfApi.login: This method is deprecated in favor of `set_access_token`.\n",
+            "Login successful\n",
+            "Your token: IsbXzzvgmnoTVFGAeeVMRdKdeivxofDKeDkNKQTkKlVoaZrNaBlZDHQXVgSxwmWopXgRtpbicOeXJVumsyxZOWGxnIqzZaWnQStFeObCthHaqDeLqbmoygwmxOrRKQmL \n",
+            "\n",
+            "Your token has been saved to /root/.huggingface/token\n"
+          ]
+        }
+      ],
+      "source": [
+        "! transformers-cli login"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Q3UPBkputdWH",
+        "outputId": "a8686c20-df9b-48d6-d6c6-24ac07223a6a"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Reading package lists... Done\n",
+            "Building dependency tree       \n",
+            "Reading state information... Done\n",
+            "The following packages were automatically installed and are no longer required:\n",
+            "  cuda-command-line-tools-10-0 cuda-command-line-tools-10-1\n",
+            "  cuda-command-line-tools-11-0 cuda-compiler-10-0 cuda-compiler-10-1\n",
+            "  cuda-compiler-11-0 cuda-cuobjdump-10-0 cuda-cuobjdump-10-1\n",
+            "  cuda-cuobjdump-11-0 cuda-cupti-10-0 cuda-cupti-10-1 cuda-cupti-11-0\n",
+            "  cuda-cupti-dev-11-0 cuda-documentation-10-0 cuda-documentation-10-1\n",
+            "  cuda-documentation-11-0 cuda-documentation-11-1 cuda-gdb-10-0 cuda-gdb-10-1\n",
+            "  cuda-gdb-11-0 cuda-gpu-library-advisor-10-0 cuda-gpu-library-advisor-10-1\n",
+            "  cuda-libraries-10-0 cuda-libraries-10-1 cuda-libraries-11-0\n",
+            "  cuda-memcheck-10-0 cuda-memcheck-10-1 cuda-memcheck-11-0 cuda-nsight-10-0\n",
+            "  cuda-nsight-10-1 cuda-nsight-11-0 cuda-nsight-11-1 cuda-nsight-compute-10-0\n",
+            "  cuda-nsight-compute-10-1 cuda-nsight-compute-11-0 cuda-nsight-compute-11-1\n",
+            "  cuda-nsight-systems-10-1 cuda-nsight-systems-11-0 cuda-nsight-systems-11-1\n",
+            "  cuda-nvcc-10-0 cuda-nvcc-10-1 cuda-nvcc-11-0 cuda-nvdisasm-10-0\n",
+            "  cuda-nvdisasm-10-1 cuda-nvdisasm-11-0 cuda-nvml-dev-10-0 cuda-nvml-dev-10-1\n",
+            "  cuda-nvml-dev-11-0 cuda-nvprof-10-0 cuda-nvprof-10-1 cuda-nvprof-11-0\n",
+            "  cuda-nvprune-10-0 cuda-nvprune-10-1 cuda-nvprune-11-0 cuda-nvtx-10-0\n",
+            "  cuda-nvtx-10-1 cuda-nvtx-11-0 cuda-nvvp-10-0 cuda-nvvp-10-1 cuda-nvvp-11-0\n",
+            "  cuda-nvvp-11-1 cuda-samples-10-0 cuda-samples-10-1 cuda-samples-11-0\n",
+            "  cuda-samples-11-1 cuda-sanitizer-11-0 cuda-sanitizer-api-10-1\n",
+            "  cuda-toolkit-10-0 cuda-toolkit-10-1 cuda-toolkit-11-0 cuda-toolkit-11-1\n",
+            "  cuda-tools-10-0 cuda-tools-10-1 cuda-tools-11-0 cuda-tools-11-1\n",
+            "  cuda-visual-tools-10-0 cuda-visual-tools-10-1 cuda-visual-tools-11-0\n",
+            "  cuda-visual-tools-11-1 default-jre dkms freeglut3 freeglut3-dev\n",
+            "  keyboard-configuration libargon2-0 libcap2 libcryptsetup12\n",
+            "  libdevmapper1.02.1 libfontenc1 libidn11 libip4tc0 libjansson4\n",
+            "  libnvidia-cfg1-510 libnvidia-common-460 libnvidia-common-510\n",
+            "  libnvidia-extra-510 libnvidia-fbc1-510 libnvidia-gl-510 libpam-systemd\n",
+            "  libpolkit-agent-1-0 libpolkit-backend-1-0 libpolkit-gobject-1-0 libxfont2\n",
+            "  libxi-dev libxkbfile1 libxmu-dev libxmu-headers libxnvctrl0 libxtst6\n",
+            "  nsight-compute-2020.2.1 nsight-compute-2022.1.0 nsight-systems-2020.3.2\n",
+            "  nsight-systems-2020.3.4 nsight-systems-2021.5.2 nvidia-dkms-510\n",
+            "  nvidia-kernel-common-510 nvidia-kernel-source-510 nvidia-modprobe\n",
+            "  nvidia-settings openjdk-11-jre policykit-1 policykit-1-gnome python3-xkit\n",
+            "  screen-resolution-extra systemd systemd-sysv udev x11-xkb-utils\n",
+            "  xserver-common xserver-xorg-core-hwe-18.04 xserver-xorg-video-nvidia-510\n",
+            "Use 'sudo apt autoremove' to remove them.\n",
+            "The following NEW packages will be installed:\n",
+            "  git-lfs\n",
+            "0 upgraded, 1 newly installed, 0 to remove and 39 not upgraded.\n",
+            "Need to get 2,129 kB of archives.\n",
+            "After this operation, 7,662 kB of additional disk space will be used.\n",
+            "Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 git-lfs amd64 2.3.4-1 [2,129 kB]\n",
+            "Fetched 2,129 kB in 1s (2,247 kB/s)\n",
+            "debconf: unable to initialize frontend: Dialog\n",
+            "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 1.)\n",
+            "debconf: falling back to frontend: Readline\n",
+            "debconf: unable to initialize frontend: Readline\n",
+            "debconf: (This frontend requires a controlling tty.)\n",
+            "debconf: falling back to frontend: Teletype\n",
+            "dpkg-preconfigure: unable to re-open stdin: \n",
+            "Selecting previously unselected package git-lfs.\n",
+            "(Reading database ... 155113 files and directories currently installed.)\n",
+            "Preparing to unpack .../git-lfs_2.3.4-1_amd64.deb ...\n",
+            "Unpacking git-lfs (2.3.4-1) ...\n",
+            "Setting up git-lfs (2.3.4-1) ...\n",
+            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
+          ]
+        }
+      ],
+      "source": [
+        "!sudo apt-get install git-lfs"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 333,
+          "referenced_widgets": [
+            "3ebed9ccd2c146c6ba9488127e6ee8a6",
+            "c7bb0364afef434c96c8bdfbf3d9e723",
+            "c6a31cfc68f043ab9d28a6d7392ea33e",
+            "5801e46d0d48481c8e514c2c140a9e8a",
+            "e0ec8eb26e904a5998b074a349772647",
+            "0ca086fa0a7845dd99a0ff45397c432e",
+            "0c2a3926fd3e4c2886cb3b8c85bd9d17",
+            "2ef25b76c6294972a086aa6e7e9e489b",
+            "cf5df892e3924d6b84f961e1ed92daa4",
+            "be3a3be2e2834515bb38c17f5afae165",
+            "126efe970315474eb54d365c5a4fdc11",
+            "f125a7ec77e94965a259da747c5e977a",
+            "8229aea668854eaf9253ef7d37b3c581",
+            "8657099513a0477cb2f9a4085676384f",
+            "282782442cd04f1e81db3c7bcaaa5053",
+            "fcb64948987d4384a60ed6fec1d9907d",
+            "5a515732569d405688f42531a82bd3cc",
+            "bf0deaa3717c4dbc9070005f43905d5d",
+            "13306c0145e841878a890cb187d8f6bc",
+            "4069f772bfe14beb82723ceb9f68a2bc",
+            "e6f8b69b6f884f90a18def2d48ba0dd4",
+            "c5fa32ca4f43447b94ec10e3c9749992",
+            "d71e5c4ed9fb42e5a6f9ac3eccdd54c3",
+            "7f1c4627865f4e599de8ea2334d82ae3",
+            "5a9d9c357b9f41298e76e02b96dc5ff2",
+            "6d0cc97c93ad43b8b442540b9aafc93d",
+            "951853a7ea9d45da823d77d26eb87bd1",
+            "aa62ff2a8172405b9245c500c3f6cf39",
+            "294f15b90016443c84a137d6bd863924",
+            "3067b686fb9245e0b5e41a029109a998",
+            "50674d7279e748b895414859de14e8bb",
+            "dce930c31d1e4240a9e6183b5d2c924f",
+            "79437dae9c214df1adebe1626251ee8e",
+            "446f2185880544f2a78595139dad32e1",
+            "c2805d4002884bf8ae1cbf2e361f6f01",
+            "ac1acf89e8fe471e835f166e7117ca9e",
+            "96b651538db14ebcb14c4c4977d8c543",
+            "be789eae91c74cfe8f64056ba0a5ba96",
+            "6c02dc0af3794da8a31d9041d3befeda",
+            "b9316e36473a4fdab62e41e495e01931",
+            "bc410fcbe11d446aa510d78100b1f3c8",
+            "3110b59b9351417da2b0e724e78ab5f3",
+            "19c8911cb3154cd5b20eebe75ddbc689",
+            "ff01c87dd90c4658b33c29cfcd07925d",
+            "58c77a53ceda434895df23b763f68199",
+            "fc94d6f1e8654303ad6dce9f25daa1fd",
+            "62f0938505354841ac2019d1f3dd95a2",
+            "0c3bfe23ae884f4ba8f8ce65a0dcaa36",
+            "16136e65fba04c7b924436ae946d90aa",
+            "e01debb97b294e639bf633f84543f344",
+            "024871a4ae304c03bc05e747e79b0ca2",
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+            "f34b8dbbcc514b18990da0d4857e256d"
+          ]
+        },
+        "id": "Q7SX18zHsLz1",
+        "outputId": "1d0cf4e4-b33d-4157-efae-478e2ead2341"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "3ebed9ccd2c146c6ba9488127e6ee8a6",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/1.87k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "f125a7ec77e94965a259da747c5e977a",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/1.02k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Downloading and preparing dataset squad_v2/squad_v2 (download: 44.34 MiB, generated: 122.41 MiB, post-processed: Unknown size, total: 166.75 MiB) to /root/.cache/huggingface/datasets/squad_v2/squad_v2/2.0.0/09187c73c1b837c95d9a249cd97c2c3f1cebada06efe667b4427714b27639b1d...\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "d71e5c4ed9fb42e5a6f9ac3eccdd54c3",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "  0%|          | 0/2 [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "446f2185880544f2a78595139dad32e1",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/9.55M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "58c77a53ceda434895df23b763f68199",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/801k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "44a4d4e42bf445be85c69a4bdb62b3d9",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "  0%|          | 0/2 [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "3b44fdcb0d2943f09fda4f13ded2f5f0",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "0 examples [00:00, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "69ea2300784a43b092eedd42a62db57c",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "0 examples [00:00, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Dataset squad_v2 downloaded and prepared to /root/.cache/huggingface/datasets/squad_v2/squad_v2/2.0.0/09187c73c1b837c95d9a249cd97c2c3f1cebada06efe667b4427714b27639b1d. Subsequent calls will reuse this data.\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "Dataset({\n",
+              "    features: ['id', 'title', 'context', 'question', 'answers'],\n",
+              "    num_rows: 130319\n",
+              "})"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from datasets import load_dataset\n",
+        "squad = load_dataset('squad_v2', split='train')\n",
+        "squad"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 145,
+          "referenced_widgets": [
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+            "67c1afb5b39a49f681c1ad71d8aee53e",
+            "9797cf4d19e443cbb9f087fc0ed57014"
+          ]
+        },
+        "id": "BbSHoYzAtoOb",
+        "outputId": "9a3fe40a-0122-4143-c130-0e55a19b67fb"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "b31d4f3bb86b43e08c492742c72b26c7",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/226k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "afb93a82b8d44c5ab708f52c4d357975",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/455k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "725fa9797d5043048eb71c48c5c3fff1",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "f0dbcb96a9944ed697f050390d8f2d16",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/570 [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "from transformers import BertTokenizerFast\n",
+        "tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 49,
+          "referenced_widgets": [
+            "4b3583ec420d49fe96296931c9b7797e",
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+            "72cb36d5fe214a5c865462a7a878b032",
+            "76055af0611a40eebb81f10a775801f2",
+            "3e60048b9fff4096afed61a58334f5bc"
+          ]
+        },
+        "id": "Dnwzl8vtttsZ",
+        "outputId": "e42635bd-bbcd-49b6-a5bb-5e583c387d37"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "4b3583ec420d49fe96296931c9b7797e",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "  0%|          | 0/130319 [00:00<?, ?ex/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "squad = squad.map(lambda x: tokenizer(\n",
+        "    x['question'], x['context'], max_length=384,\n",
+        "    padding='max_length', truncation=True,\n",
+        "    return_offsets_mapping=True\n",
+        "))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 158
+        },
+        "id": "Nw8UgKO4tve1",
+        "outputId": "01f84237-793e-488b-b2d0-db6a7ab55215"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            },
+            "text/plain": [
+              "'[CLS] when did beyonce start becoming popular? [SEP] beyonce giselle knowles - carter ( / biːˈjɒnseɪ / bee - yon - say ) ( born september 4, 1981 ) is an american singer, songwriter, record producer and actress. born and raised in houston, texas, she performed in various singing and dancing competitions as a child, and rose to fame in the late 1990s as lead singer of r & b girl - group destiny\\'s child. managed by her father, mathew knowles, the group became one of the world\\'s best - selling girl groups of all time. their hiatus saw the release of beyonce\\'s debut album, dangerously in love ( 2003 ), which established her as a solo artist worldwide, earned five grammy awards and featured the billboard hot 100 number - one singles \" crazy in love \" and \" baby boy \". [SEP] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD] [PAD]'"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "tokenizer.decode(squad[0]['input_ids'])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "J0tnhaDkt42r",
+        "outputId": "0c9ba7d8-5dc7-4995-bf5a-3c769c1b7be1"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(9, 165)"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "question_len = 0\n",
+        "for x in squad[0]['token_type_ids']:\n",
+        "    if x != 1:\n",
+        "        question_len += 1\n",
+        "    else: break\n",
+        "context_len = sum(squad[0]['token_type_ids'])\n",
+        "question_len, context_len"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "id": "KASMBMlnt9dT"
+      },
+      "outputs": [],
+      "source": [
+        "def char_to_id(sample):\n",
+        "    # find the question length\n",
+        "    try:\n",
+        "        char_start = sample['answers']['answer_start'][0]\n",
+        "        sample['answers']['answer_end'] = sample['answers']['answer_start'][0] + len(sample['answers']['text'][0])\n",
+        "        char_end = sample['answers']['answer_end']\n",
+        "    except:\n",
+        "        char_start = 0\n",
+        "        char_end = 0\n",
+        "    question_len = 0\n",
+        "    for x in sample['token_type_ids']:\n",
+        "        if x != 1:\n",
+        "            question_len += 1\n",
+        "        else: break\n",
+        "    # and get the context length\n",
+        "    context_len = sum(sample['token_type_ids'])\n",
+        "    # get offset mappings for context segment\n",
+        "    context_mappings = sample['offset_mapping'][question_len:][:context_len-1]\n",
+        "    for i, mapping in enumerate(context_mappings):\n",
+        "        if char_start >= mapping[0] and char_start <= mapping[1]:\n",
+        "            token_start = question_len + i\n",
+        "        if char_end >= mapping[0] and char_end <= mapping[1]:\n",
+        "            token_end = question_len + i + 1\n",
+        "            return {'start_positions': token_start, 'end_positions': token_end}\n",
+        "        if i == len(context_mappings) - 1:\n",
+        "            # this means the answer tokens are out of range, eg have been truncated\n",
+        "            # and therefore there is no answer\n",
+        "            token_start, token_end = 0, 0\n",
+        "            return {'start_positions': token_start, 'end_positions': token_end}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 49,
+          "referenced_widgets": [
+            "6057cd879aec4905919c0a6e0306b1f1",
+            "ec58f280e1b9414a9265791ec8f5b37e",
+            "28f2ded5887c4e7993b12540660aa31c",
+            "61d4664e38cd48af9744dc4ad2408fc2",
+            "6fb7e8b206c546649fd1236ebbd49521",
+            "efb3d53bc4614ceea4fabab0502f316f",
+            "d38311b80b2c477b980ec4b16343bbcc",
+            "9af6e6f204b849ef8fe5f717c8d7f438",
+            "7d23dfc9860e48e3a2e20d4c7d9e6ef3",
+            "06d527b80eeb479e8aa7e05b367b3679",
+            "8dfea51f1c8b4eca825cd7ec8bf7e961"
+          ]
+        },
+        "id": "yCpYQzafuHDk",
+        "outputId": "bb5d7cd8-e2b4-4fef-9a9c-512c70932d95"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "6057cd879aec4905919c0a6e0306b1f1",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "  0%|          | 0/130319 [00:00<?, ?ex/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "squad = squad.map(lambda x: char_to_id(x))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "_xHEHiV6yNAd",
+        "outputId": "ae4f83d5-8cba-408f-cd0d-ae553b7afded"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Dataset({\n",
+              "    features: ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions'],\n",
+              "    num_rows: 130319\n",
+              "})"
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "squad = squad.remove_columns(['id', 'title', 'context', 'question', 'answers', 'offset_mapping'])\n",
+        "squad"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 156,
+          "referenced_widgets": [
+            "16a53f95b9c341d79e5d3ed3b85e65de",
+            "08f59828064544ec8ce8b719650246a6",
+            "6d0bf959219841288b19267fb2b11d09",
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+            "d6de66281631467cbaa7b80bdae40783",
+            "b730ec07396b478497708d7a5ccb599a"
+          ]
+        },
+        "id": "IQTJsfYMuNh4",
+        "outputId": "8780d2fd-27de-41d0-fa20-6b86ae58881d"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "16a53f95b9c341d79e5d3ed3b85e65de",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading:   0%|          | 0.00/420M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForQuestionAnswering: ['cls.predictions.transform.LayerNorm.bias', 'cls.predictions.bias', 'cls.seq_relationship.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.weight', 'cls.predictions.decoder.weight']\n",
+            "- This IS expected if you are initializing BertForQuestionAnswering from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
+            "- This IS NOT expected if you are initializing BertForQuestionAnswering from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
+            "Some weights of BertForQuestionAnswering were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['qa_outputs.weight', 'qa_outputs.bias']\n",
+            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
+          ]
+        }
+      ],
+      "source": [
+        "from transformers import default_data_collator\n",
+        "from transformers import BertForQuestionAnswering\n",
+        "data_collator = default_data_collator\n",
+        "model = BertForQuestionAnswering.from_pretrained('bert-base-uncased')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "yNO9Y-TLuUHc",
+        "outputId": "2e17752d-3860-4290-cc91-636d1e290ae6"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/transformers/training_args.py:926: FutureWarning: `--push_to_hub_model_id` is deprecated and will be removed in version 5 of 🤗 Transformers. Use `--hub_model_id` instead and pass the full repo name to this argument (in this case Vasanth/bert-base-uncased-qa-squad2).\n",
+            "  FutureWarning,\n"
+          ]
+        }
+      ],
+      "source": [
+        "from transformers import TrainingArguments\n",
+        "\n",
+        "batch_size = 24\n",
+        "epochs = 3\n",
+        "\n",
+        "args = TrainingArguments(\n",
+        "    'bert-base-uncased-qa-squad2',\n",
+        "    learning_rate=3e-5,\n",
+        "    per_device_train_batch_size=batch_size,\n",
+        "    num_train_epochs=epochs,\n",
+        "    weight_decay=0.1,\n",
+        "    warmup_steps=int(len(squad)*epochs*0.1),\n",
+        "    push_to_hub_model_id=\"bert-base-uncased-qa-squad2\",\n",
+        "    push_to_hub=True\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "yIhXYC7Qu7C8",
+        "outputId": "3c9e3940-2793-4a67-c593-4f97deaac259"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Cloning https://huggingface.co/Vasanth/bert-base-uncased-qa-squad2 into local empty directory.\n",
+            "***** Running training *****\n",
+            "  Num examples = 130319\n",
+            "  Num Epochs = 3\n",
+            "  Instantaneous batch size per device = 24\n",
+            "  Total train batch size (w. parallel, distributed & accumulation) = 24\n",
+            "  Gradient Accumulation steps = 1\n",
+            "  Total optimization steps = 16290\n"
+          ]
+        }
+      ],
+      "source": [
+        "from transformers import Trainer\n",
+        "import torch\n",
+        "\n",
+        "device = 'cuda:0' if torch.cuda.is_available() else 'cpu'\n",
+        "\n",
+        "trainer = Trainer(\n",
+        "    model.to(device),\n",
+        "    args,\n",
+        "    train_dataset=squad,\n",
+        "    data_collator=data_collator,\n",
+        "    tokenizer=tokenizer\n",
+        ")\n",
+        "trainer.train()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "D_kdX2o7vbva"
+      },
+      "outputs": [],
+      "source": [
+        "trainer.push_to_hub()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "xXwWF6ppvRXr"
+      },
+      "outputs": [],
+      "source": [
+        "trainer.save_model('bert-base-uncased-qa-squad2')"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "name": "Reader.ipynb",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
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