Create_WikiSplit_in_format.ipynb

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      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/bhadreshpsavani/t5-sentence-split/blob/main/Create_WikiSplit_in_format.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q--9LpTp3XTk",
        "outputId": "98f5969a-c5f8-4863-c98a-72d069b278f9"
      },
      "source": [
        "!pip install datasets\n",
        "!pip install transformers"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: datasets in /usr/local/lib/python3.7/dist-packages (1.9.0)\n",
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            "Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from datasets) (4.5.0)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2018.9)\n",
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            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (3.0.4)\n",
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            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n",
            "Collecting transformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/fd/1a/41c644c963249fd7f3836d926afa1e3f1cc234a1c40d80c5f03ad8f6f1b2/transformers-4.8.2-py3-none-any.whl (2.5MB)\n",
            "\u001b[K     |████████████████████████████████| 2.5MB 26.6MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers) (2.23.0)\n",
            "Collecting huggingface-hub==0.0.12\n",
            "  Downloading https://files.pythonhosted.org/packages/2f/ee/97e253668fda9b17e968b3f97b2f8e53aa0127e8807d24a547687423fe0b/huggingface_hub-0.0.12-py3-none-any.whl\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (1.19.5)\n",
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            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from transformers) (20.9)\n",
            "Collecting tokenizers<0.11,>=0.10.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/d4/e2/df3543e8ffdab68f5acc73f613de9c2b155ac47f162e725dcac87c521c11/tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3MB)\n",
            "\u001b[K     |████████████████████████████████| 3.3MB 36.0MB/s \n",
            "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (2019.12.20)\n",
            "Collecting sacremoses\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/75/ee/67241dc87f266093c533a2d4d3d69438e57d7a90abb216fa076e7d475d4a/sacremoses-0.0.45-py3-none-any.whl (895kB)\n",
            "\u001b[K     |████████████████████████████████| 901kB 33.4MB/s \n",
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            "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->transformers) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2.10)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from huggingface-hub==0.0.12->transformers) (3.7.4.3)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers) (3.4.1)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->transformers) (2.4.7)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.0.1)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (7.1.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.15.0)\n",
            "Installing collected packages: huggingface-hub, tokenizers, sacremoses, transformers\n",
            "  Found existing installation: huggingface-hub 0.0.13\n",
            "    Uninstalling huggingface-hub-0.0.13:\n",
            "      Successfully uninstalled huggingface-hub-0.0.13\n",
            "Successfully installed huggingface-hub-0.0.12 sacremoses-0.0.45 tokenizers-0.10.3 transformers-4.8.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
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          ]
        },
        "id": "UhZ5Gx543IMX",
        "outputId": "3adb5a11-b8c4-4434-86eb-4ffa852321e3"
      },
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "dataset = load_dataset(\"wiki_split\")"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "884ac145f59a4280b924dbc0541405e1",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1528.0, style=ProgressStyle(description…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "299ed13ee90f4a6997e9dc4cecceebcc",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1089.0, style=ProgressStyle(description…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "Using custom data configuration default\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Downloading and preparing dataset wiki_split/default (download: 95.63 MiB, generated: 370.41 MiB, post-processed: Unknown size, total: 466.04 MiB) to /root/.cache/huggingface/datasets/wiki_split/default/0.1.0/83151e5f3f5a622601303c2f562ffda5502643e38f3f1fee48999d0030f82b07...\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "42a20411f0dc4bd88d1218ad5c450a67",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=96439435.0, style=ProgressStyle(descrip…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f946bd5db06f40f2bff6711590135bb2",
              "version_minor": 0,
              "version_major": 2
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            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=525160.0, style=ProgressStyle(descripti…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "93b89ad4c4f9495db28bc307865efb5c",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=519665.0, style=ProgressStyle(descripti…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "0e3d3789a6ae4e2ca56121307d978d22",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\r"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "643ecc4d65444348b607cb2e468acb4b",
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              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\r"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "943546cb457540e7aa30f248ce724938",
              "version_minor": 0,
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              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\rDataset wiki_split downloaded and prepared to /root/.cache/huggingface/datasets/wiki_split/default/0.1.0/83151e5f3f5a622601303c2f562ffda5502643e38f3f1fee48999d0030f82b07. Subsequent calls will reuse this data.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "De7F7QIU3Wwa",
        "outputId": "8bc7a289-9b1d-4e46-e4ea-d3c93abfbf4b"
      },
      "source": [
        "dataset"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatasetDict({\n",
              "    train: Dataset({\n",
              "        features: ['complex_sentence', 'simple_sentence_1', 'simple_sentence_2'],\n",
              "        num_rows: 989944\n",
              "    })\n",
              "    test: Dataset({\n",
              "        features: ['complex_sentence', 'simple_sentence_1', 'simple_sentence_2'],\n",
              "        num_rows: 5000\n",
              "    })\n",
              "    validation: Dataset({\n",
              "        features: ['complex_sentence', 'simple_sentence_1', 'simple_sentence_2'],\n",
              "        num_rows: 5000\n",
              "    })\n",
              "})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KvrhFW1m3l5T",
        "outputId": "3f249519-0512-48d6-9c3f-b25e8c8a1e5e"
      },
      "source": [
        "train_dataset = dataset['train']\n",
        "train_dataset"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['complex_sentence', 'simple_sentence_1', 'simple_sentence_2'],\n",
              "    num_rows: 989944\n",
              "})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 137,
          "referenced_widgets": [
            "4f8bf4299e9044dfa86fa139c81b20f4",
            "222465f7cb6a4d97a54506332d925a33",
            "fde7b825e4464796881ee9909c04f392",
            "56889faea8a7450aae7b989566886e1d",
            "7e2b1a612e954f69a741e9d278d133a1",
            "93a3ae4912d24ab0ba4a85e8cafd45f6",
            "711c19dd51d7419d8c5eb44619f02718",
            "98497d0777bf4c83b9e466205a599c19"
          ]
        },
        "id": "gEHqrEUg4nhi",
        "outputId": "2946c5ba-7740-4746-cc9d-6d9dc76dccec"
      },
      "source": [
        "train_dataset = train_dataset.map(lambda x: {\"complex_sentence\": \"sentence split: \"+x[\"complex_sentence\"]})\n",
        "train_dataset"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4f8bf4299e9044dfa86fa139c81b20f4",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=989944.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['complex_sentence', 'simple_sentence_1', 'simple_sentence_2'],\n",
              "    num_rows: 989944\n",
              "})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "a15a18d248cf478c8fc0339b25994413",
            "85acf20afa484cf7851721b7e1a9cd59",
            "7575a81dcb844963b1cb0d507212cfb5",
            "8997d6d110c74fef92d268dcfb0a8f5f",
            "592ffc0ed5ad42a0a16d637151ed6d36",
            "4fea83fc7f784388aea8d48e293c43f7",
            "480414adacad45dab0df7eaade5c1c34",
            "8fc223ab4ba34c7182fb34484728367a"
          ]
        },
        "id": "H7CexW5w55pM",
        "outputId": "4adfe707-2d74-491c-b9fd-f16508b7db8b"
      },
      "source": [
        "train_dataset = train_dataset.map(\n",
        "    lambda x: {\"target_sentences\": x[\"simple_sentence_1\"]+ \" <::::> \" +x[\"simple_sentence_2\"]}, \n",
        "    remove_columns=['simple_sentence_1', 'simple_sentence_2'])"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a15a18d248cf478c8fc0339b25994413",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=989944.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6FGu0n6x5MU7",
        "outputId": "6e7ec859-bcb2-4ef0-81e1-577273928531"
      },
      "source": [
        "train_dataset[0]"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'complex_sentence': \"sentence split: ' '' As she translates from one language to another , she tries to find the appropriate wording and context in English that would correspond to the work in Spanish her poems and stories started to have differing meanings in their respective languages .\",\n",
              " 'target_sentences': \"' '' As she translates from one language to another , she tries to find the appropriate wording and context in English that would correspond to the work in Spanish .  <::::>  Ergo , her poems and stories started to have differing meanings in their respective languages .\"}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ArM6-Z4q7oXi",
        "outputId": "fc17ea43-be28-4c27-88aa-7c7a09d21d0d"
      },
      "source": [
        "train_dataset.to_csv('train_file.csv', index=False))"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "405840406"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84,
          "referenced_widgets": [
            "cff59d9b766047dfbcfc7d454982cfef",
            "38f2defb012f4e8b9db64ea1c6a946ca",
            "4daf99101ec844bca150ccc463a3357c",
            "eededff73b304ca99752b6cbb5ad585e",
            "1e5f04b9099042da940c337902ddb4ea",
            "27ca27af182e4c5e8b7b94e02efdbbfb",
            "22987cf89fe94b74be1d3c225b2380dc",
            "4c763a4a9eb040a3a7f621048f1973a6"
          ]
        },
        "id": "sfY4MTAR776t",
        "outputId": "dfc9784a-6dd7-442f-d894-dc982faf8f24"
      },
      "source": [
        "train_dataset.to_json('train_file.json', index=False))"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "cff59d9b766047dfbcfc7d454982cfef",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=99.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "442515120"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pjjxfd1E36Pl",
        "outputId": "5c70df10-a7d9-44a1-dbb5-c3be902a18e5"
      },
      "source": [
        "validation_dataset = dataset['validation']\n",
        "validation_dataset"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['complex_sentence', 'simple_sentence_1', 'simple_sentence_2'],\n",
              "    num_rows: 5000\n",
              "})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166,
          "referenced_widgets": [
            "4049ee2c116b4673bcc605daf0a2132b",
            "5ed5922a0e194d1a9c90c63e85ce6a95",
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            "aa0ef28deab34c8f8aa663a6b3d50d42",
            "3a337b33156e4e6d85557a0176b276db",
            "e381cd33f5b249699f528c35d7c7072b",
            "738c234a36574f8cb52a547bf7c86b69",
            "ee6b0e77a3fa4fa99192b88ce2eacc2c",
            "8ce3c4c36c2a4deeae4b13c74a139e31",
            "eee4d240c88d4fe299ef0a5dd7c998db",
            "a0699f594ce348dab060f06bad882151",
            "ca67efa6500c40a3bca3803f78b672b6",
            "4c2984c24a944d089c79e0ca826823f4",
            "ec17bfc0bcba4009977b129c8a629d13",
            "22445d7f65584283ae48a87ab8ca4e08",
            "dfc4f15501bf41e081c52e72334588f9",
            "14ade6dbd8d24703af8798bb30296780",
            "1ed106e1244142259d7649df6970fd03",
            "db5d9600c7164b61911fc2a53be78494",
            "b91e8f4a1abe434ea2be93b27eac4ce9",
            "0c818cfbd3284441b06abc457f270ce6"
          ]
        },
        "id": "YWJyYPbi3_ur",
        "outputId": "d6ae3d76-3865-4f52-ef28-d8a205fc0cfc"
      },
      "source": [
        "from transformers import AutoTokenizer, AutoModelWithLMHead\n",
        "  \n",
        "tokenizer = AutoTokenizer.from_pretrained(\"t5-base\")\n",
        "\n",
        "# model = AutoModelWithLMHead.from_pretrained(\"t5-base\")"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4049ee2c116b4673bcc605daf0a2132b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1199.0, style=ProgressStyle(description…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "e381cd33f5b249699f528c35d7c7072b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=791656.0, style=ProgressStyle(descripti…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ec17bfc0bcba4009977b129c8a629d13",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1389353.0, style=ProgressStyle(descript…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZYvfCwkJ4Sbj"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}