Lao_Word2Vec.ipynb

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  },
  "cells": [
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      "cell_type": "markdown",
      "metadata": {
        "id": "LwwOptiWYvYF"
      },
      "source": [
        "# Lao Word Embedding using Word2Vec\n",
        "\n",
        "Data from https://traces1.inria.fr/oscar/\n",
        "\n",
        "Python | Word Embedding using Word2Vec https://www.geeksforgeeks.org/python-word-embedding-using-word2vec/"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install datasets laonlp tqdm"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "isTDtuIdfdcF",
        "outputId": "2e7e74b5-1a2d-4f6d-dc93-cb1589b466de"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: datasets in /usr/local/lib/python3.7/dist-packages (2.3.2)\n",
            "Requirement already satisfied: laonlp in /usr/local/lib/python3.7/dist-packages (0.6)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (4.64.0)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from datasets) (1.3.5)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.7/dist-packages (from datasets) (3.8.1)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from datasets) (1.21.6)\n",
            "Requirement already satisfied: fsspec[http]>=2021.05.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (2022.5.0)\n",
            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (2.23.0)\n",
            "Requirement already satisfied: huggingface-hub<1.0.0,>=0.1.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (0.8.1)\n",
            "Requirement already satisfied: xxhash in /usr/local/lib/python3.7/dist-packages (from datasets) (3.0.0)\n",
            "Requirement already satisfied: responses<0.19 in /usr/local/lib/python3.7/dist-packages (from datasets) (0.18.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from datasets) (21.3)\n",
            "Requirement already satisfied: dill<0.3.6 in /usr/local/lib/python3.7/dist-packages (from datasets) (0.3.5.1)\n",
            "Requirement already satisfied: multiprocess in /usr/local/lib/python3.7/dist-packages (from datasets) (0.70.13)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from datasets) (4.12.0)\n",
            "Requirement already satisfied: pyarrow>=6.0.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (6.0.1)\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) (4.1.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.7.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (6.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->datasets) (3.0.9)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (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) (1.25.11)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (2022.6.15)\n",
            "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",
            "Requirement already satisfied: pythainlp>=2.1.0 in /usr/local/lib/python3.7/dist-packages (from laonlp) (3.0.8)\n",
            "Requirement already satisfied: tinydb>=3.0 in /usr/local/lib/python3.7/dist-packages (from pythainlp>=2.1.0->laonlp) (4.7.0)\n",
            "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (2.1.0)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (21.4.0)\n",
            "Requirement already satisfied: asynctest==0.13.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (0.13.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (6.0.2)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (1.3.0)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (1.7.2)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (1.2.0)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (4.0.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->datasets) (3.8.0)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2022.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2.8.2)\n",
            "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"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from laonlp.tokenize import word_tokenize,sent_tokenize"
      ],
      "metadata": {
        "id": "zoL03eLyf6PP"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "02IeHfwwWuq0"
      },
      "source": [
        "import gensim \n",
        "from gensim.models import Word2Vec "
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0A4Hhhs4W-C_"
      },
      "source": [
        "from datasets import load_dataset"
      ],
      "execution_count": 4,
      "outputs": []
    },
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            "4175b0f0a5324be8b095fa7d1e400a7e",
            "7cb677cd33c04a4080a6da45d2c35409",
            "da4551a3482648f1ba45c3b3d7292b2c",
            "143d501a6ed5456daae50a992b99fd04",
            "20b69f0248ca43a181039cb0c2c0490f",
            "d774369aefdb4603b1d3bb642860f231",
            "3c7a09c89d3844c1b87ec65b8213f35d",
            "da40bdd763154430904a385fb18eadd9",
            "d1a7a01720cc4a21b4715fa554e8a336",
            "62136e11d86a493ea41e0cef6635de4d",
            "c78f7ace31d44e25b51e3318a02094f9",
            "7a0b2c1bdcbc4fe3a2180d33f82f6493",
            "f2fbec9a610341d08fa2328c7e278502",
            "0bc2a5e6b6cf43f7bc82b1eb32d01bb6",
            "f089f223e8c44e8abab065d313175fcd",
            "430749f8ca33456babc2480f81d508c6",
            "78651d34220a43329a9dd8ca0a438141",
            "3cacd553b00742228b5cf665c50a82e8",
            "5de2074e6e124e66ba47dd8efd698854",
            "c3e3d9f22f0947cd886ccec5f88febfd",
            "e42725821f604b6a86b941b103344d97",
            "988cfd19b9744bf0a7f3fe231ccf6225",
            "f54170e7c41d45ae84416de3fd0b19b9"
          ]
        },
        "outputId": "94de06a2-1042-4421-9f80-6d0564013634"
      },
      "source": [
        "dataset = load_dataset(\"oscar\", \"unshuffled_deduplicated_lo\")"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading and preparing dataset oscar/unshuffled_deduplicated_lo (download: 22.54 MiB, generated: 113.50 MiB, post-processed: Unknown size, total: 136.04 MiB) to /root/.cache/huggingface/datasets/oscar/unshuffled_deduplicated_lo/1.0.0/84838bd49d2295f62008383b05620571535451d84545037bb94d6f3501651df2...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/81.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "65598ffd8e7942f49de40acfc457033a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data files:   0%|          | 0/1 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4bfd784abfec47c2bbf417644887ba56"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/23.6M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "74b21d4cbb474a0fa3af6fb1d4a63894"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating train split:   0%|          | 0/32652 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7cb677cd33c04a4080a6da45d2c35409"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset oscar downloaded and prepared to /root/.cache/huggingface/datasets/oscar/unshuffled_deduplicated_lo/1.0.0/84838bd49d2295f62008383b05620571535451d84545037bb94d6f3501651df2. Subsequent calls will reuse this data.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/1 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f2fbec9a610341d08fa2328c7e278502"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZeCQ933AXLym",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 110
        },
        "outputId": "dd8367e8-9ddc-4f63-901f-e0d77d149dfb"
      },
      "source": [
        "dataset['train']['text'][0:1][0]"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'ວີ\\u200bໂອ\\u200bເອພາກ\\u200bພາສາ\\u200bລາວ\\u200b ກະຈາຍສຽງ\\u200bທຸກໆ\\u200bວັນ \\u200bເປັນ\\u200bເວລາ 30 ນາທີ. ພວກ\\u200bເຮົາ\\u200bສະ\\u200bເໜີຂ່າວ ຂໍ້\\u200bມູນ \\u200bແລະ\\u200bລາຍ\\u200bງານ\\u200bທີ່\\u200bໜ້າ\\u200bສົນ\\u200bໃຈ ກ່ຽວກັບ\\u200b\\u200bເຫດການ\\u200b\\u200bທີ່\\u200bເກີດ\\u200bຂຶ້ນ\\u200bໃນ\\u200bປະ\\u200bເທດ\\u200bລາວ ສະຫະລັດ\\u200bອ\\u200bາ\\u200bເມ\\u200bຣິ\\u200bກາ \\u200bເອ\\u200bເຊຍ\\u200bແລະ\\u200bຂົງເຂດ\\u200bອື່ນໆ\\u200bຂອງ\\u200bໂລກ ຕະຫລອດ\\u200bທັງ\\u200bບົດຮຽນ\\u200bພາສາ\\u200bອັງກິດ \\u200bແລະ\\u200bລາຍການ\\u200bເພງ\\u200bຕາມ\\u200bຄຳ\\u200bຂໍ\\u200bຂອງ\\u200bທ່ານ\\u200bຜູ້\\u200bຟັງ.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset['train']['text'][0:1][0].replace('\\u200b', '').strip()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "dFtDGECfglLt",
        "outputId": "f20f3f73-630c-41f7-8d5a-8da437a86219"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'ວີໂອເອພາກພາສາລາວ ກະຈາຍສຽງທຸກໆວັນ ເປັນເວລາ 30 ນາທີ. ພວກເຮົາສະເໜີຂ່າວ ຂໍ້ມູນ ແລະລາຍງານທີ່ໜ້າສົນໃຈ ກ່ຽວກັບເຫດການທີ່ເກີດຂຶ້ນໃນປະເທດລາວ ສະຫະລັດອາເມຣິກາ ເອເຊຍແລະຂົງເຂດອື່ນໆຂອງໂລກ ຕະຫລອດທັງບົດຮຽນພາສາອັງກິດ ແລະລາຍການເພງຕາມຄຳຂໍຂອງທ່ານຜູ້ຟັງ.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "[i.strip() for i in sent_tokenize(dataset['train']['text'][0:1][0].replace('\\u200b', '').strip()) if i!='']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K_ystPtCg-RI",
        "outputId": "0a863f69-ab70-4948-d4bb-6241a704225a"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['ວີໂອເອພາກພາສາລາວ ກະຈາຍສຽງທຸກໆວັນ ເປັນເວລາ 30 ນາທີ',\n",
              " 'ພວກເຮົາສະເໜີຂ່າວ ຂໍ້ມູນ ແລະລາຍງານທີ່ໜ້າສົນໃຈ ກ່ຽວກັບເຫດການທີ່ເກີດຂຶ້ນໃນປະເທດລາວ ສະຫະລັດອາເມຣິກາ ເອເຊຍແລະຂົງເຂດອື່ນໆຂອງໂລກ ຕະຫລອດທັງບົດຮຽນພາສາອັງກິດ ແລະລາຍການເພງຕາມຄຳຂໍຂອງທ່ານຜູ້ຟັງ']"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "[word_tokenize(i.strip()) for i in sent_tokenize(dataset['train']['text'][0:1][0].replace('\\u200b', '').strip()) if i!='']"
      ],
      "metadata": {
        "id": "yqgbWlIqhQ1-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from tqdm.auto import tqdm"
      ],
      "metadata": {
        "id": "-rgmeQWuhlPz"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sents=[]\n",
        "for j in tqdm(list(dataset['train']['text'])):\n",
        "  sents.extend([word_tokenize(i.strip()) for i in sent_tokenize(j.replace('\\u200b', '').strip()) if i!=''])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "86f1673f19bf43c9b8851465b8e90729",
            "4cf39cd99f43492d8fe47878c507b519",
            "10312e4763cb4b2486881e0a44dc1f80",
            "cf97c2da51224248b6161b971842faeb",
            "ab1cedc0ab684278b1c45c281504341a",
            "170356e5de0b44fcbb1d9836f2c81077",
            "815e383e635a49269052b2fdb1f51425",
            "dcd2b4099b59438c9a76d47a7aef3146",
            "24e8a43340bb4dd3883abb40e1fcc8b0",
            "980e07164797469a9d4d2b33a174743b",
            "e63799351ff349fbb219e2cc0059c73f"
          ]
        },
        "id": "tKWtdGf5hMJs",
        "outputId": "0a267cb8-8aef-4e0e-d3ef-00d09648ff66"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/32652 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "86f1673f19bf43c9b8851465b8e90729"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "08-hb0aiXmex",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7a5deefd-20e0-4dd3-ecdf-32bcee952ee4"
      },
      "source": [
        "len(sents)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "239449"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sents[0:2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oo57pbUci3UT",
        "outputId": "f22208e7-662c-4168-d7ae-c4f0b9d2ccd3"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['ວີໂອ',\n",
              "  'ເອ',\n",
              "  'ພາກ',\n",
              "  'ພາສາລາວ',\n",
              "  ' ',\n",
              "  'ກະຈາຍສຽງ',\n",
              "  'ທຸກ',\n",
              "  'ໆ',\n",
              "  'ວັນ',\n",
              "  ' ',\n",
              "  'ເປັນ',\n",
              "  'ເວລາ',\n",
              "  ' ',\n",
              "  '30',\n",
              "  ' ',\n",
              "  'ນາທີ'],\n",
              " ['ພວກເຮົາ',\n",
              "  'ສະເໜີ',\n",
              "  'ຂ່າວ',\n",
              "  ' ',\n",
              "  'ຂໍ້ມູນ',\n",
              "  ' ',\n",
              "  'ແລະ',\n",
              "  'ລາຍງານທີ່',\n",
              "  'ໜ້າ',\n",
              "  'ສົນໃຈ',\n",
              "  ' ',\n",
              "  'ກ່ຽວກັບ',\n",
              "  'ເຫດການທີ່ເກີດຂຶ້ນ',\n",
              "  'ໃນປະເທດລາວ',\n",
              "  ' ',\n",
              "  'ສະຫະລັດ',\n",
              "  'ອາເມຣິກາ',\n",
              "  ' ',\n",
              "  'ເອເຊຍ',\n",
              "  'ແລະ',\n",
              "  'ຂົງເຂດ',\n",
              "  'ອື່ນ',\n",
              "  'ໆ',\n",
              "  'ຂອງ',\n",
              "  'ໂລກ',\n",
              "  ' ',\n",
              "  'ຕະຫລອດ',\n",
              "  'ທັງ',\n",
              "  'ບົດຮຽນ',\n",
              "  'ພາສາອັງກິດ',\n",
              "  ' ',\n",
              "  'ແລະ',\n",
              "  'ລາຍການ',\n",
              "  'ເພງ',\n",
              "  'ຕາມ',\n",
              "  'ຄຳ',\n",
              "  'ຂໍ',\n",
              "  'ຂອງ',\n",
              "  'ທ່ານ',\n",
              "  'ຜູ້ຟັງ']]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9QBaT78XXcjF"
      },
      "source": [
        "data = []"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PL7FTncdXe2C",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "40d412bb6d0b4cbaae31449f51ff87ad",
            "a03c020912494e3688bd38474e2546c0",
            "d22971b79eb5447dabb420084494b186",
            "2ae6b2e4058a434fa1ccb2ad4f4a1d25",
            "42afcb65930242dfa173e568c2c7291e",
            "a7f36745cb764d83a664261dffdb0f0f",
            "127ebd17cfad4e839bbe8a849206b1c3",
            "53f16034546e4250aea171b84c7ae96c",
            "e6b47ff5e07b4e99bff49805250b7f63",
            "a038087c26aa4463b40fc6be1afb8caa",
            "6c3439420aab44ab8361ea0a26ca9bc7"
          ]
        },
        "outputId": "1aa5c6ff-94a8-4d5a-fefc-9ee25ae727a4"
      },
      "source": [
        "# iterate through each sentence in the file \n",
        "for i in tqdm(sents): \n",
        "    temp = [] \n",
        "      \n",
        "    # tokenize the sentence into words \n",
        "    for j in i:\n",
        "        temp.append(j.lower()) \n",
        "  \n",
        "    data.append(temp)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/239449 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "40d412bb6d0b4cbaae31449f51ff87ad"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PwdT43doXUZu"
      },
      "source": [
        "#CBOW model\n",
        "model = gensim.models.Word2Vec(data, min_count = 1,  \n",
        "                              size = 300, window = 5) "
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8D0pYkSFbDHT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5bec4ffc-04ec-4dd9-d7d2-5ffe721b0748"
      },
      "source": [
        "print(\"Cosine similarity between 'ວຽງຈັນ' \" +\n",
        "          \"and 'ເມືອງ' - CBOW model : \", \n",
        "    model.wv.similarity('ວຽງຈັນ', 'ເມືອງ')) "
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cosine similarity between 'ວຽງຈັນ' and 'ເມືອງ' - CBOW model :  0.3162512\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KybdqK1BYS0F"
      },
      "source": [
        "# Skip Gram model \n",
        "model2 = gensim.models.Word2Vec(data, min_count = 1, size = 300, \n",
        "                                             window = 5, sg = 1) "
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pojeG4PBaQSg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dd442aa9-7785-4587-fc98-3e626fea36db"
      },
      "source": [
        "print(\"Cosine similarity between 'ວຽງຈັນ' \" +\n",
        "          \"and 'ເມືອງ' - Skip Gram : \", \n",
        "    model2.wv.similarity('ວຽງຈັນ', 'ເມືອງ')) "
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cosine similarity between 'ວຽງຈັນ' and 'ເມືອງ' - Skip Gram :  0.46474797\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xMTFG9aOdVt_"
      },
      "source": [
        "model.wv.save_word2vec_format('lao_oscar_cbow_model.bin', binary=True)"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model2.wv.save_word2vec_format('lao_oscar_skipgram_model.bin', binary=True)"
      ],
      "metadata": {
        "id": "i84wuZ-Vl1Aw"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "Y0lOTFnml_oI"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}