Run_segmentation_colab.ipynb

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  "metadata": {
    "colab": {
      "name": "Run on Colab.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMfKD8SDWCMowMgYSYYdEgf",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rinabuoy/KhmerNLP/blob/master/Run_segmentation_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "code",
      "metadata": {
        "id": "jfJaMvXitusB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 134
        },
        "outputId": "fab591bb-317b-4830-f1eb-9e0ec6830bc4"
      },
      "source": [
        "! git clone https://github.com/rinabuoy/KhmerNLP"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'KhmerNLP'...\n",
            "remote: Enumerating objects: 26, done.\u001b[K\n",
            "remote: Counting objects:   3% (1/26)\u001b[K\rremote: Counting objects:   7% (2/26)\u001b[K\rremote: Counting objects:  11% (3/26)\u001b[K\rremote: Counting objects:  15% (4/26)\u001b[K\rremote: Counting objects:  19% (5/26)\u001b[K\rremote: Counting objects:  23% (6/26)\u001b[K\rremote: Counting objects:  26% (7/26)\u001b[K\rremote: Counting objects:  30% (8/26)\u001b[K\rremote: Counting objects:  34% (9/26)\u001b[K\rremote: Counting objects:  38% (10/26)\u001b[K\rremote: Counting objects:  42% (11/26)\u001b[K\rremote: Counting objects:  46% (12/26)\u001b[K\rremote: Counting objects:  50% (13/26)\u001b[K\rremote: Counting objects:  53% (14/26)\u001b[K\rremote: Counting objects:  57% (15/26)\u001b[K\rremote: Counting objects:  61% (16/26)\u001b[K\rremote: Counting objects:  65% (17/26)\u001b[K\rremote: Counting objects:  69% (18/26)\u001b[K\rremote: Counting objects:  73% (19/26)\u001b[K\rremote: Counting objects:  76% (20/26)\u001b[K\rremote: Counting objects:  80% (21/26)\u001b[K\rremote: Counting objects:  84% (22/26)\u001b[K\rremote: Counting objects:  88% (23/26)\u001b[K\rremote: Counting objects:  92% (24/26)\u001b[K\rremote: Counting objects:  96% (25/26)\u001b[K\rremote: Counting objects: 100% (26/26)\u001b[K\rremote: Counting objects: 100% (26/26), done.\u001b[K\n",
            "remote: Compressing objects: 100% (17/17), done.\u001b[K\n",
            "remote: Total 215 (delta 9), reused 20 (delta 9), pack-reused 189\u001b[K\n",
            "Receiving objects: 100% (215/215), 378.34 KiB | 1.41 MiB/s, done.\n",
            "Resolving deltas: 100% (79/79), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yXermZhSuTvu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "a58f0b90-fdc3-4fc4-a19e-4e881af62663"
      },
      "source": [
        "%cd KhmerNLP"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/KhmerNLP\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T2n8DEaFnxfm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 168
        },
        "outputId": "ffd7d24c-6ea2-4b59-9f1e-40088ab92f1b"
      },
      "source": [
        "!pip install wget"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting wget\n",
            "  Downloading https://files.pythonhosted.org/packages/47/6a/62e288da7bcda82b935ff0c6cfe542970f04e29c756b0e147251b2fb251f/wget-3.2.zip\n",
            "Building wheels for collected packages: wget\n",
            "  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for wget: filename=wget-3.2-cp36-none-any.whl size=9682 sha256=ceaaa337b18a7f475e1958d2583f1d9169c6ac9f66c49f33668285c394d8eb7d\n",
            "  Stored in directory: /root/.cache/pip/wheels/40/15/30/7d8f7cea2902b4db79e3fea550d7d7b85ecb27ef992b618f3f\n",
            "Successfully built wget\n",
            "Installing collected packages: wget\n",
            "Successfully installed wget-3.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EvI6wJtVAL1F",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 205
        },
        "outputId": "bb11152d-5677-4983-a694-200620b1ebc5"
      },
      "source": [
        "!pip install sklearn_crfsuite"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting sklearn_crfsuite\n",
            "  Downloading https://files.pythonhosted.org/packages/25/74/5b7befa513482e6dee1f3dd68171a6c9dfc14c0eaa00f885ffeba54fe9b0/sklearn_crfsuite-0.3.6-py2.py3-none-any.whl\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from sklearn_crfsuite) (1.15.0)\n",
            "Requirement already satisfied: tabulate in /usr/local/lib/python3.6/dist-packages (from sklearn_crfsuite) (0.8.7)\n",
            "Requirement already satisfied: tqdm>=2.0 in /usr/local/lib/python3.6/dist-packages (from sklearn_crfsuite) (4.41.1)\n",
            "Collecting python-crfsuite>=0.8.3\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/95/99/869dde6dbf3e0d07a013c8eebfb0a3d30776334e0097f8432b631a9a3a19/python_crfsuite-0.9.7-cp36-cp36m-manylinux1_x86_64.whl (743kB)\n",
            "\u001b[K     |████████████████████████████████| 747kB 10.7MB/s \n",
            "\u001b[?25hInstalling collected packages: python-crfsuite, sklearn-crfsuite\n",
            "Successfully installed python-crfsuite-0.9.7 sklearn-crfsuite-0.3.6\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DelI0WVlu3YP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67
        },
        "outputId": "fec83582-f98f-4857-8cd7-4d38f8725593"
      },
      "source": [
        "from khmerwordsegmentor import segment\n",
        "ts = \"ចំណែកជើងទី២ នឹងត្រូវធ្វើឡើងឯប្រទេសកាតា៕\"\n",
        "print('Segmention by LSTM: ', segment(ts,model='lstm'))\n",
        "print('Segmention by CRF: ', segment(ts,model='crf'))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Inference on GPU!\n",
            "Segmention by LSTM:  ចំណែក-ជើង-ទី-២-នឹង-ត្រូវ-ធ្វើឡើង-ឯ-ប្រទេស-កាតា-៕\n",
            "Segmention by CRF:  ចំណែកជើង-ទី-២-នឹង-ត្រូវ-ធ្វើឡើង-ឯ-ប្រទេស-កាតា-៕\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}