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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "from datasets import load_dataset\n",
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+ "\n",
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+ "dataset = load_dataset(\"divyasharma0795/AppleVisionPro_Tweets\")"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "HuggingFaceDataset(id=1769458624638619691, tweetText=\"Mordecai I can't sell nft for 10 dollars, how does this nft business work? #bloodbath #AppleVisionPro #DeadpoolAndWolverine #RegularShow @JGQuintel link: https://t.co/Bq3dzV4wgR https://t.co/rbrerIFcIs\", tweetURL='https://twitter.com/harndefty/status/1769458624638619691', tweetAuthor='Harndefty 🐔🍗', handle='@harndefty', replyCount=0, quoteCount=0, retweetCount=0, likeCount=0, views='26', bookmarkCount=0, createdAt='2024-03-17 13:19:45')\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "from dataclasses import dataclass\n",
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+ "from typing import List\n",
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+ "from datasets import load_dataset\n",
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+ "\n",
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+ "\n",
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+ "@dataclass\n",
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+ "class HuggingFaceDataset:\n",
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+ " id: int\n",
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+ " tweetText: str\n",
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+ " tweetURL: str\n",
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+ " tweetAuthor: str\n",
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+ " handle: str\n",
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+ " replyCount: int\n",
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+ " quoteCount: int\n",
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+ " retweetCount: int\n",
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+ " likeCount: int\n",
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+ " views: int\n",
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+ " bookmarkCount: int\n",
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+ " createdAt: str\n",
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+ "\n",
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+ "\n",
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+ "def load_custom_dataset(dataset_name):\n",
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+ " dataset = load_dataset(dataset_name)\n",
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+ "\n",
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+ " # Extract relevant information and create a list of HuggingFaceDataset instances\n",
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+ " custom_dataset = [\n",
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+ " HuggingFaceDataset(\n",
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+ " id=row[\"id\"],\n",
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+ " tweetText=row[\"tweetText\"],\n",
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+ " tweetURL=row[\"tweetURL\"],\n",
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+ " tweetAuthor=row[\"tweetAuthor\"],\n",
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+ " handle=row[\"handle\"],\n",
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+ " replyCount=row[\"replyCount\"],\n",
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+ " quoteCount=row[\"quoteCount\"],\n",
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+ " retweetCount=row[\"retweetCount\"],\n",
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+ " likeCount=row[\"likeCount\"],\n",
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+ " views=row[\"views\"],\n",
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+ " bookmarkCount=row[\"bookmarkCount\"],\n",
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+ " createdAt=row[\"createdAt\"],\n",
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+ " )\n",
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+ " for row in dataset[\"train\"]\n",
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+ " ]\n",
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+ "\n",
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+ " return custom_dataset\n",
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+ "\n",
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+ "\n",
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+ "# Usage\n",
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+ "custom_dataset = load_custom_dataset(\"divyasharma0795/AppleVisionPro_Tweets\")\n",
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+ "print(custom_dataset[0]) # Print the first instance"
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+ ]
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "base",
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+ "language": "python",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.11.5"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 2
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+ }