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" Attempting uninstall: markdown-it-py\n", - " Found existing installation: markdown-it-py 3.0.0\n", - " Uninstalling markdown-it-py-3.0.0:\n", - " Successfully uninstalled markdown-it-py-3.0.0\n", - " Attempting uninstall: mdit-py-plugins\n", - " Found existing installation: mdit-py-plugins 0.4.0\n", - " Uninstalling mdit-py-plugins-0.4.0:\n", - " Successfully uninstalled mdit-py-plugins-0.4.0\n", - "Successfully installed aiofiles-23.2.1 fastapi-0.101.1 ffmpy-0.3.1 gradio-3.40.1 gradio-client-0.4.0 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 orjson-3.9.4 pydub-0.25.1 python-multipart-0.0.6 semantic-version-2.10.0 starlette-0.27.0 uvicorn-0.23.2 websockets-11.0.3\n" - ] - } - ] - }, - { - "cell_type": "code", - "source": [ - "import warnings\n", - "warnings.filterwarnings('ignore')" - ], - "metadata": { - "id": "KrWFRhcIwlr2" - }, - "execution_count": 2, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "from google.colab import drive\n", - "drive.mount('/content/drive')" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "QWd5xNcZPSwf", - "outputId": "af0865f0-1c83-47cd-c2cd-38887bf8bfa8" - }, - "execution_count": 3, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n" - ] - } - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "id": "1y2hQdL9v2H2" - }, - "outputs": [], - "source": [ - "#import all reqiured package\n", - "import numpy as np\n", - "import pandas as pd\n", - "import seaborn as sns\n", - "import re\n", - "import torch\n", - "import random\n", - "import torch.nn as nn\n", - "import transformers\n", - "from transformers import BertModel, BertTokenizer, AdamW, get_linear_schedule_with_warmup\n", - "import matplotlib.pyplot as plt\n", - "from torch.utils.data import Dataset, DataLoader\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import confusion_matrix, classification_report\n", - "from collections import defaultdict\n", - "import pickle\n", - "from tqdm import tqdm\n", - "import gradio as gr" - ] - }, - { - "cell_type": "code", - "source": [ - "# specify GPU\n", - "device = torch.device(\"cuda\")" - ], - "metadata": { - "id": "Z1B3lorSPnOg" - }, - "execution_count": 5, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "The code employs the BERT language model for breaking down text into tokens and translating them into numerical IDs. Initially, the chosen BERT model, 'bert-base-cased', is set, and a tokenizer is initialized accordingly.\n", - "\n", - "Subsequently, the script takes a sample text, \"originally gave this a 2 star,\" and processes it through the tokenizer. This procedure involves transforming the text into a sequence of tokens, which are the fundamental units that BERT comprehends." - ], - "metadata": { - "id": "1-Kk65MVPpHW" - } - }, - { - "cell_type": "code", - "source": [ - "MODEL_NAME = 'bert-base-cased'\n", - "tokenizer = transformers.BertTokenizer.from_pretrained(MODEL_NAME)\n", - "\n", - "sample_text = \"originally gave this a 2 star\"\n", - "\n", - "tokens = tokenizer.tokenize(sample_text)\n", - "ids = tokenizer.convert_tokens_to_ids(tokens)\n", - "print(f'{sample_text}')\n", - "print('='*60)\n", - "print(tokens)\n", - "print('='*60)\n", - "print(ids)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 200, - "referenced_widgets": [ - "b4fc2c984f2645018de746f5d8a797ce", - "e7d1f445ef554aed8822694d1f8359da", - "ee98241475ba45b286f06419a5e6f98e", - "a26e3b24701b404c9a4ecfe5254e80a7", - "5653f8a132284815ba6024eaa630bb99", - "cdcda9f0bd3f46c7a4bdfded45c5a337", - "92ae8f417c194689b37737c202beb775", - "26927005165346aa88afe05c526ffbd5", - "8cf6d499de9240caac68361f47c827c2", - "8e375f57951945f8b30a3221feb1c321", - "44a626e31a174c0999eb69c020c73ccf", - "4f9828add59f42d88df8e5e05bca6d35", - "8f95fd57907c4535bd85368ffe919cee", - "108684ab8406424fa36a50fd9e83963f", - "9c312b06a55c4e92a6bd849f7eb26c1b", - "3493bc8db73146d2ae94de22e1a10cbb", - "5e9670b2fb3b46499154c27d3a22c30e", - "1911a60f265a4f20919b7331b18d0a65", - "bf9441545b514803af65596ed8e1ccf3", - "d8f6b777fd3b4c4484d51fcdc63548d4", - "cfcc1efafcd64f67a6eb04697e6a2e36", - "ab8d32d5b535443eae20205157a71632", - "90034728af564f3cb3eee515f39d7e14", - "367b25f9e63a45c2bcfcc115512fa229", - "9ed3184b1e374bd69f427dd000d0c194", - "00b55aa69c05491e8cf8a8d450d76ca7", - "d951bdcf4b0146a8abde000546a8aaf6", - "42c2016023204f16a694e5f7ba74ccb2", - "9bf04a48ab8e4552957f37af2a171760", - "08015c83e858438e93e6f294b96e2ac5", - "04f35e81be6648bf962eaae1b95e7c8b", - "105eb4205ede46c5b80884f5b523c182", - "5a4590edde474f68951201b1a6e21f3d" - ] - }, - "id": "I_MkvDNtv-CL", - "outputId": "e821d206-3607-4bf5-b85b-05e158760d1a" - }, - "execution_count": 6, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "Downloading (…)solve/main/vocab.txt: 0%| | 0.00/213k [00:00" - ], - "text/html": [ - "
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