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import csv |
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import datasets |
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import os |
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_DESCRIPTION = "TODO" |
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_HOMEPAGE = "TODO" |
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_LICENSE = "TODO" |
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_URL = {"UltimateArabic":"https://huggingface.co/datasets/khalidalt/ultimate_arabic_news/blob/main/UltimateArabic.csv","UltimateArabicPrePros":"https://huggingface.co/datasets/khalidalt/ultimate_arabic_news/raw/main/UltimateArabicPrePros.csv"} |
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class UAN_Config(datasets.BuilderConfig): |
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"""BuilderConfig for Ultamte Arabic News""" |
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def __init__(self, **kwargs): |
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""" |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(UAN_Config, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) |
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class Ultimate_Arabic_News(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.1.0") |
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BUILDER_CONFIGS = [ |
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UAN_Config( |
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name="UltimateArabic", |
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description=textwrap.dedent( |
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"""\ |
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UltimateArabic: A file containing more than 193,000 original Arabic news texts, without pre-processing. The texts contain words, |
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numbers, and symbols that can be removed using pre-processing to increase accuracy when using the dataset in various Arabic natural |
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language processing tasks such as text classification.""" |
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), |
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), |
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UAN_Config( |
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name="UltimateArabicPrePros", |
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description=textwrap.dedent( |
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"""UltimateArabicPrePros: It is a file that contains the data mentioned in the first file, but after pre-processing, where |
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the number of data became about 188,000 text documents, where stop words, non-Arabic words, symbols and numbers have been |
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removed so that this file is ready for use directly in the various Arabic natural language processing tasks. Like text |
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classification. |
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""" |
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), |
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), |
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] |
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