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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/aryan0931/Youtube-video-summarizer/blob/main/Untitled5.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pr_pSaVUfgPd",
        "outputId": "b58e7bdc-3a01-491c-afaa-dbdc1ef2e074"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/57.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.6/57.6 kB\u001b[0m \u001b[31m1.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip install pytube -q"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pytube import YouTube"
      ],
      "metadata": {
        "id": "4ZshmjVgfo9P"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "VIDEO_URL = 'https://www.youtube.com/watch?v=h-JVjs9AAmQ'"
      ],
      "metadata": {
        "id": "TF2rMDPgfpAE"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "yt = YouTube(VIDEO_URL)"
      ],
      "metadata": {
        "id": "3nt7UtBNfpC3"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "yt.streams \\\n",
        "  .filter(only_audio = True, file_extension = 'mp4') \\\n",
        "  .first() \\\n",
        "  .download(filename = 'ytaudio.mp4')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "sbYbDCW2fpFa",
        "outputId": "e267b0d9-9d95-47e5-8e03-81f56d8b03cd"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/ytaudio.mp4'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! ffmpeg -i ytaudio.mp4 -acodec pcm_s16le -ar 16000 ytaudio.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WCeiHr33fpML",
        "outputId": "722b0bea-66f0-4580-f081-0d1dad4b9f01"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
            "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
            "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
            "  libavutil      56. 70.100 / 56. 70.100\n",
            "  libavcodec     58.134.100 / 58.134.100\n",
            "  libavformat    58. 76.100 / 58. 76.100\n",
            "  libavdevice    58. 13.100 / 58. 13.100\n",
            "  libavfilter     7.110.100 /  7.110.100\n",
            "  libswscale      5.  9.100 /  5.  9.100\n",
            "  libswresample   3.  9.100 /  3.  9.100\n",
            "  libpostproc    55.  9.100 / 55.  9.100\n",
            "Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'ytaudio.mp4':\n",
            "  Metadata:\n",
            "    major_brand     : dash\n",
            "    minor_version   : 0\n",
            "    compatible_brands: iso6mp41\n",
            "    creation_time   : 2022-03-03T20:20:21.000000Z\n",
            "  Duration: 00:04:15.65, start: 0.000000, bitrate: 48 kb/s\n",
            "  Stream #0:0(eng): Audio: aac (HE-AAC) (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 1 kb/s (default)\n",
            "    Metadata:\n",
            "      creation_time   : 2022-03-03T20:20:21.000000Z\n",
            "      handler_name    : ISO Media file produced by Google Inc.\n",
            "      vendor_id       : [0][0][0][0]\n",
            "Stream mapping:\n",
            "  Stream #0:0 -> #0:0 (aac (native) -> pcm_s16le (native))\n",
            "Press [q] to stop, [?] for help\n",
            "Output #0, wav, to 'ytaudio.wav':\n",
            "  Metadata:\n",
            "    major_brand     : dash\n",
            "    minor_version   : 0\n",
            "    compatible_brands: iso6mp41\n",
            "    ISFT            : Lavf58.76.100\n",
            "  Stream #0:0(eng): Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, stereo, s16, 512 kb/s (default)\n",
            "    Metadata:\n",
            "      creation_time   : 2022-03-03T20:20:21.000000Z\n",
            "      handler_name    : ISO Media file produced by Google Inc.\n",
            "      vendor_id       : [0][0][0][0]\n",
            "      encoder         : Lavc58.134.100 pcm_s16le\n",
            "size=   15978kB time=00:04:15.65 bitrate= 512.0kbits/s speed= 265x    \n",
            "video:0kB audio:15978kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.000477%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install huggingsound -q"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y6W5lHZMfpVA",
        "outputId": "9eaf1f2a-d883-4631-ce18-d8477d02955d"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/521.2 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━\u001b[0m \u001b[32m491.5/521.2 kB\u001b[0m \u001b[31m14.9 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m521.2/521.2 kB\u001b[0m \u001b[31m11.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m214.3/214.3 kB\u001b[0m \u001b[31m12.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m776.3/776.3 MB\u001b[0m \u001b[31m715.6 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m13.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m16.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.2/2.2 MB\u001b[0m \u001b[31m56.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.1/3.1 MB\u001b[0m \u001b[31m63.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchaudio 2.1.0+cu118 requires torch==2.1.0, but you have torch 1.12.1 which is incompatible.\n",
            "torchdata 0.7.0 requires torch==2.1.0, but you have torch 1.12.1 which is incompatible.\n",
            "torchtext 0.16.0 requires torch==2.1.0, but you have torch 1.12.1 which is incompatible.\n",
            "torchvision 0.16.0+cu118 requires torch==2.1.0, but you have torch 1.12.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from huggingsound import SpeechRecognitionModel"
      ],
      "metadata": {
        "id": "hrJY56iZfpff"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
      ],
      "metadata": {
        "id": "8RlYAdhCiTk0"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "device"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "_gyUY1abiTsX",
        "outputId": "2f47e667-f2a9-44db-a98b-f7adb242591a"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'cpu'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = SpeechRecognitionModel(\"jonatasgrosman/wav2vec2-large-xlsr-53-english\", device = device)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195,
          "referenced_widgets": [
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        "id": "rANLY8IKiVhT",
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      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:huggingsound.speech_recognition.model:Loading model...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/1.53k [00:00<?, ?B/s]"
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              "version_major": 2,
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          "metadata": {}
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        {
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          "data": {
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              "model.safetensors:   0%|          | 0.00/1.26G [00:00<?, ?B/s]"
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "preprocessor_config.json:   0%|          | 0.00/262 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "153398762eb94ce58186972e4e92b7da"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "vocab.json:   0%|          | 0.00/300 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6e420544fdec43a68a8963d8c501a43d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/85.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1ae95adb3ea647108e42a16f73c21cba"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import librosa"
      ],
      "metadata": {
        "id": "OmM8knFLiVkC"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "input_file = '/content/ytaudio.wav'"
      ],
      "metadata": {
        "id": "ba1Hmnl2iVmv"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(librosa.get_samplerate(input_file))\n",
        "\n",
        "# Stream over 30 seconds chunks rather than load the full file\n",
        "stream = librosa.stream(\n",
        "    input_file,\n",
        "    block_length=30,\n",
        "    frame_length=16000,\n",
        "    hop_length=16000\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PEZSGQFWipIl",
        "outputId": "f7413ef8-3a25-40cf-f196-2e2c478f756c"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "16000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import soundfile as sf"
      ],
      "metadata": {
        "id": "qn_y1jEuipPJ"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i,speech in enumerate(stream):\n",
        "  sf.write(f'{i}.wav', speech, 16000)"
      ],
      "metadata": {
        "id": "DHW6lBYJjW4c"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "i"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CFKCZqYkjW7O",
        "outputId": "ba8e996a-5ef0-45ef-dcee-7815710d2085"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "audio_path =[]\n",
        "for a in range(i+1):\n",
        "  audio_path.append(f'/content/{a}.wav')\n",
        "\n",
        "audio_path"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sRqoEXVmjc8i",
        "outputId": "d6a33ff5-af2e-4bea-f7f5-88090b4584e4"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['/content/0.wav',\n",
              " '/content/1.wav',\n",
              " '/content/2.wav',\n",
              " '/content/3.wav',\n",
              " '/content/4.wav',\n",
              " '/content/5.wav',\n",
              " '/content/6.wav',\n",
              " '/content/7.wav',\n",
              " '/content/8.wav']"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "transcriptions = model.transcribe(audio_path)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nidbjwj7jc_X",
        "outputId": "6cc8da37-fa69-41bc-86ea-ec4ed3d2596c"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 9/9 [06:10<00:00, 41.14s/it]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_transcript = ' '"
      ],
      "metadata": {
        "id": "xhpoj3MajdBo"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for item in transcriptions:\n",
        "  full_transcript += ''.join(item['transcription'])"
      ],
      "metadata": {
        "id": "AA0tjkazjdD6"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(full_transcript)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zPJ2vA4PjW9w",
        "outputId": "e1fab82a-08de-4a60-a45d-60ab414b81de"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3091"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Text summarization\n"
      ],
      "metadata": {
        "id": "9MjPd8zrkvln"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline"
      ],
      "metadata": {
        "id": "V_Oi4HMqipU2"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "summarization = pipeline('summarization')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233,
          "referenced_widgets": [
            "4075f606b6224dbaa2b089edcbb10dd8",
            "fc46857359ef4a7885a9fa08b0698261",
            "8655b6a75a0a4fadbdce2a9d352d4ae9",
            "a8186200316347878de5a5feda673c54",
            "63dfddd4b9c84cbab36f68e4ab56bc54",
            "8651cb8023f847b9952a986c17467fab",
            "30d429184b2644d68e821bf6cda8a41e",
            "8552dd9fcc5744359d0074ac9ee2ce57",
            "a13f72f5be7047c9a50a8bc93851e405",
            "ff5c50715cee43c28a6c82c267b7947f",
            "abae4a45ca8244d988e63f1f22dab68e",
            "d6f3e03c0e6c4dc0acc0040ee6bbfaf8",
            "3cb9da6a22524f22abad442c231802fd",
            "de37f01a1f614c89a668db496a27682d",
            "f0170b7c5958428c9219f90f1e13079c",
            "21093122aba74a649d499e8b8e5bb805",
            "6a2212163309459ea8247b4f490cdd8a",
            "3860177381b644d49c10a73b9a902175",
            "ae4e531b3b604ca98821f5a103b4c519",
            "e2a245af245c42019e8296489687c099",
            "11c43b8f617840d0b3e0aa25112de3d8",
            "b9679244645340699216a90ff7243695",
            "076af243598f40f18674ac0801c84265",
            "3c51bda57b92490eabf4c6096a24b9cc",
            "e2a17634b9a04e329461107b399f913e",
            "f1511f79b3f54270a7b4a50968b99536",
            "bc5f81221abe42c5a16e462aca402a4d",
            "ee3004afd91c40e6bf025255d75f087b",
            "1045d7f656b8462cb73fc419d10fbb12",
            "21bd80cee7b64abbba3f88e6edca5789",
            "0039ef5528f04de19586fd23bb0365bb",
            "71c98b64af6542fabda6ec69538a697f",
            "f5d171d3621f424dae6c248c1d37dc75",
            "dd7ec7f16bc24dc3a6f8366ee6ba9f06",
            "4dd2209cd3bf4f77961fa310a9fd3f2a",
            "0fe6fc87c5d345799afcd27266cb3425",
            "2775fc7a6b0b4a898f5b8055c4a9e556",
            "072242cfa25445299ee52eeadde7f86c",
            "c7aa4b64081f46c59c6c7059c9c14a45",
            "2c606f4a3ecf4184b9fcfa83cca049d9",
            "89a33bc8821d4a22a402e84de2547917",
            "5bb9b2db99bc422facbe3c0db83a028b",
            "5d82461da14244c7a156324f7a8042cd",
            "3068a95dda9e4f068ee9a7741c107951",
            "64a22c7749c148d28cb5cc3a0ca9278c",
            "23523f20255649f8a06144978c42ccee",
            "4f070858093344a8bd3e3482b2757bb1",
            "175b57615e6f45f8895f679426ca8b21",
            "51c9a0a1ea1e422db6023f12686d216d",
            "f330fcdcee8a44f28dd43be6ebc1f624",
            "2a2c49a8d947450eba1639be23c13f61",
            "2bd273b702d74160bdca0f9c81ec2720",
            "2a4c7d21e0db4d5480b93ce286cf778f",
            "30f786cae63b420cb6d0b91cd1437d1f",
            "ad29956c07ad472eab848be32257f02a"
          ]
        },
        "id": "vBHvs9EBk5DD",
        "outputId": "279ddcef-a4a7-48db-ddb1-0c4d34def713"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to sshleifer/distilbart-cnn-12-6 and revision a4f8f3e (https://huggingface.co/sshleifer/distilbart-cnn-12-6).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/1.80k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4075f606b6224dbaa2b089edcbb10dd8"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "pytorch_model.bin:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d6f3e03c0e6c4dc0acc0040ee6bbfaf8"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/26.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "076af243598f40f18674ac0801c84265"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "vocab.json:   0%|          | 0.00/899k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "dd7ec7f16bc24dc3a6f8366ee6ba9f06"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "64a22c7749c148d28cb5cc3a0ca9278c"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "summarized_text = summarization(full_transcript)"
      ],
      "metadata": {
        "id": "3HZczNjLlkpn"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "summarized_text[0]['summary_text']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "id": "Xk_go4Oak5Fk",
        "outputId": "84487596-6d32-4923-c6c2-7d4a86e64b82"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\" The role of cat woman has been played by litedary access arears from rto kit and shell fifer . Batman is about etwo sides of drauma batman's born of trama andtis film maybes the ridler and tat is kind of the seed from which everything else grew .\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "num_iters = int(len(full_transcript)/1000)\n",
        "summarized_text = []\n",
        "for i in range(0, num_iters + 1):\n",
        "  start = 0\n",
        "  start = i * 1000\n",
        "  end = (i + 1) * 1000\n",
        "  #print(\"input text \\n\" + full_transcript[start:end])\n",
        "  out = summarization(full_transcript[start:end], min_length = 5, max_length=20)\n",
        "  out = out[0]\n",
        "  out = out['summary_text']\n",
        "  print(\"Summarized text\\n\"+out)\n",
        "  summarized_text.append(out)\n",
        "  #print(summarized_text)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a6PpPYY-k5IM",
        "outputId": "30861087-5316-4cd1-b079-889685de8f6c"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Summarized text\n",
            " The role of cat woman has been played by litedary access arears from r\n",
            "Summarized text\n",
            " The key was really trying to trust that mt chose me for a reason realso i\n",
            "Summarized text\n",
            " \"Pinguwin\" was truly something spectacular so new onts very interesting do you\n",
            "Summarized text\n",
            " Le bit that that that made it interesting for me so yet ided lot of people\n"
          ]
        }
      ]
    }
  ]
}