Sentiment_Analysis_with_Prebuilt_flair_Models.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/rajni-arora/Deep-Learning-Projects/blob/main/Sentiment_Analysis_with_Prebuilt_flair_Models.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hmoq2Vup62N2"
      },
      "source": [
        "# **Language Classification**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ivkut00K6Gqa"
      },
      "source": [
        "1. Initialize the model\n",
        "2. Tokenizind\n",
        "3. Process with model\n",
        "4. Format the outputs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KQh1bM5z7Kvt"
      },
      "source": [
        "!pip install flair"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wptLbd8n9xP2"
      },
      "source": [
        "Download and Initialize the model"
      ]
    },
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        "id": "4dTuemfG6CSL",
        "outputId": "8b2c012c-102b-431b-97e2-9509a7e6e7a8"
      },
      "source": [
        "#Here we are loading a Text Classifier, en-sentiment = Englist sentiment model\n",
        "import flair\n",
        "model  = flair.models.TextClassifier.load('en-sentiment')"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2021-08-20 09:47:04,254 https://nlp.informatik.hu-berlin.de/resources/models/sentiment-curated-distilbert/sentiment-en-mix-distillbert_4.pt not found in cache, downloading to /tmp/tmpm14m08r8\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 265512723/265512723 [00:09<00:00, 27969184.50B/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "2021-08-20 09:47:14,068 copying /tmp/tmpm14m08r8 to cache at /root/.flair/models/sentiment-en-mix-distillbert_4.pt\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "2021-08-20 09:47:14,554 removing temp file /tmp/tmpm14m08r8\n",
            "2021-08-20 09:47:14,591 loading file /root/.flair/models/sentiment-en-mix-distillbert_4.pt\n"
          ],
          "name": "stdout"
        },
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              "Downloading:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"
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        },
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "joxOiXDs-TRe"
      },
      "source": [
        "Tokenizing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BK8q0yhZ7JTU",
        "outputId": "54f821ac-6a4c-476e-d9fc-432459f5c61d"
      },
      "source": [
        "text = 'I like you!'\n",
        "\n",
        "sentence = flair.data.Sentence(text)\n",
        "\n",
        "sentence"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sentence: \"I like you !\"   [− Tokens: 4]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "9Kdhkekb-dTq",
        "outputId": "ed9a723c-8dc0-4542-9362-fed33a9321cc"
      },
      "source": [
        "#If want to seperate by space\n",
        "sentence.to_tokenized_string()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'I like you !'"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "la0KUi14_Qw2"
      },
      "source": [
        "Process with model\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MgpX8wAr_MUJ"
      },
      "source": [
        "#process our tokenized inputs through out the DISTILL BERT Classifier\n",
        "model.predict(sentence)\n"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2D9kEyv_A6Ff",
        "outputId": "d29a8f83-5d17-4709-e25c-ef31d67d031c"
      },
      "source": [
        "sentence #We can see it added labels"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sentence: \"I like you !\"   [− Tokens: 4  − Sentence-Labels: {'label': [POSITIVE (0.9928)]}]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ptaU1Uh7A_aF",
        "outputId": "ec269950-b34d-4f91-d251-cf5bbc09cc55"
      },
      "source": [
        "#Try Negative Sentence\n",
        "text = 'I hate it when i am not learning about ML'\n",
        "sentence = flair.data.Sentence(text)\n",
        "model.predict(sentence)\n",
        "sentence"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sentence: \"I hate it when i am not learning about ML\"   [− Tokens: 10  − Sentence-Labels: {'label': [NEGATIVE (0.9995)]}]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WePF_vyXBhCN",
        "outputId": "5ba66022-74a8-43da-9623-7f1b0be8076b"
      },
      "source": [
        "#List containing labels \n",
        "sentence.get_labels()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[NEGATIVE (0.9995)]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vIpe1oq8CAwY",
        "outputId": "0413e45e-6bd5-45be-b49d-ced521431f59"
      },
      "source": [
        "#List at 0 index\n",
        "sentence.get_labels()[0]"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "NEGATIVE (0.9995)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SQSh0JdGCH23",
        "outputId": "4fde2260-8f3a-4892-c979-291bab378453"
      },
      "source": [
        "help(sentence.get_labels()[0])"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Help on Label in module flair.data object:\n",
            "\n",
            "class Label(builtins.object)\n",
            " |  Label(value: str, score: float = 1.0)\n",
            " |  \n",
            " |  This class represents a label. Each label has a value and optionally a confidence score. The\n",
            " |  score needs to be between 0.0 and 1.0. Default value for the score is 1.0.\n",
            " |  \n",
            " |  Methods defined here:\n",
            " |  \n",
            " |  __init__(self, value: str, score: float = 1.0)\n",
            " |      Initialize self.  See help(type(self)) for accurate signature.\n",
            " |  \n",
            " |  __repr__(self)\n",
            " |      Return repr(self).\n",
            " |  \n",
            " |  __str__(self)\n",
            " |      Return str(self).\n",
            " |  \n",
            " |  to_dict(self)\n",
            " |  \n",
            " |  ----------------------------------------------------------------------\n",
            " |  Data descriptors defined here:\n",
            " |  \n",
            " |  __dict__\n",
            " |      dictionary for instance variables (if defined)\n",
            " |  \n",
            " |  __weakref__\n",
            " |      list of weak references to the object (if defined)\n",
            " |  \n",
            " |  score\n",
            " |  \n",
            " |  value\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cjXyqUdsCXrD",
        "outputId": "1c593e62-23b7-4a93-f903-c4d339b80928"
      },
      "source": [
        "#Getting prediction\n",
        "sentence.get_labels()[0].score"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9994839429855347"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "fBWkY3UHCaCl",
        "outputId": "db210f06-0767-49cf-eb47-a483c4760fbe"
      },
      "source": [
        "#Getting Values\n",
        "sentence.get_labels()[0].value"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'NEGATIVE'"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZssmusKgCoAT",
        "outputId": "92675525-f386-4d7f-f26e-89b5bb71a49d"
      },
      "source": [
        "sentence.get_labels()[0].score,sentence.get_labels()[0].value"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0.9994839429855347, 'NEGATIVE')"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8gn6jj8yDH8e"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}