Emoji.ipynb

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  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ICy5TLNliLgK",
        "outputId": "1ad43533-702e-4f35-9cb4-d974e44ae047"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "😀\n"
          ]
        }
      ],
      "source": [
        "print(\"\\U0001f600\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"\\U0001f606\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hMXQ9olqi6uE",
        "outputId": "687f8347-dea3-4c4e-c3b7-bf2a86ff055c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "😆\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"\\U0001f923\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4QJn4bc7jI8y",
        "outputId": "651efe8f-1969-40e8-d9ad-b21e29a01053"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "🤣\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"\\N{grinning face}\")\n",
        "print(\"\\N{slightly smiling face}\")\n",
        "print(\"\\N{winking face}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZRISAlG5jPKi",
        "outputId": "b799bd1b-9f6e-41f4-aadd-eb4e96bd8742"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "😀\n",
            "🙂\n",
            "😉\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install emoji --upgrade"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TUYoHo2KkPbO",
        "outputId": "3b9cade2-614e-4eb0-d22f-e1449efdd374"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting emoji\n",
            "  Downloading emoji-2.1.0.tar.gz (216 kB)\n",
            "\u001b[K     |████████████████████████████████| 216 kB 3.2 MB/s \n",
            "\u001b[?25hBuilding wheels for collected packages: emoji\n",
            "  Building wheel for emoji (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for emoji: filename=emoji-2.1.0-py3-none-any.whl size=212392 sha256=57f2698ad524f67953c82e095635995c10304af8d47788b641cf53337671377b\n",
            "  Stored in directory: /root/.cache/pip/wheels/77/75/99/51c2a119f4cfd3af7b49cc57e4f737bed7e40b348a85d82804\n",
            "Successfully built emoji\n",
            "Installing collected packages: emoji\n",
            "Successfully installed emoji-2.1.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import emoji\n",
        "print(emoji.emojize('Hi there! :heart_decoration:'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6yQ09STzkaXt",
        "outputId": "710d5bfc-591b-4a1b-e5c1-465a86a6dc79"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hi there! 💟\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(emoji.emojize(\":grinning_face_with_big_eyes:\"))\n",
        "print(emoji.emojize(\":smiling_cat_with_heart-eyes:\"))\n",
        "print(emoji.emojize(\":zipper-mouth_face:\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PCCFcUA3k9-1",
        "outputId": "46ab3059-a373-484a-f4b8-6904dcb8fb16"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "😃\n",
            "😻\n",
            "🤐\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q transformers\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H30e2c31mk-I",
        "outputId": "8993b764-7355-448c-85f1-12a51ac57513"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[K     |████████████████████████████████| 4.9 MB 2.6 MB/s \n",
            "\u001b[K     |████████████████████████████████| 6.6 MB 40.9 MB/s \n",
            "\u001b[K     |████████████████████████████████| 120 kB 57.4 MB/s \n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline\n",
        "sentiment_pipeline = pipeline(\"sentiment-analysis\")\n",
        "data = [\"I LOVE NOBODY\",\"TODAY IS A BORING DAY\"]\n",
        "sentiment_pipeline(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uuqgRzxUm5o4",
        "outputId": "159de9c6-ff02-4fca-b24a-a6f8d4593a55"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'label': 'NEGATIVE', 'score': 0.9963550567626953},\n",
              " {'label': 'NEGATIVE', 'score': 0.9994691014289856}]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "specific_model = pipeline(model='finiteautomata/bertweet-base-sentiment-analysis')\n",
        "specific_model(data)"
      ],
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          "height": 308,
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              "Downloading:   0%|          | 0.00/890 [00:00<?, ?B/s]"
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading:   0%|          | 0.00/17.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5ffd15542b0e42debe6d91d3af0b21b8"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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              "model_id": "6cd63d2ad3e54e3aab5c8c2ccb911547"
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          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'label': 'POS', 'score': 0.9905869364738464},\n",
              " {'label': 'NEG', 'score': 0.9813030362129211}]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from textblob import TextBlob\n",
        "testimonial = TextBlob(\"I am hungry\")\n",
        "print(testimonial.sentiment)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d7wugjA9p8pV",
        "outputId": "3daec778-3aeb-42ef-8f3f-86587beb1ead"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment(polarity=0.0, subjectivity=0.0)\n"
          ]
        }
      ]
    }
  ]
}