Delete caner_replicate.py

caner_replicate.py

@@ -1,119 +0,0 @@
-# -*- coding: utf-8 -*-
-"""caner_replicate.ipynb
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1QgToSf5_B5l43oRCKwI2vGEB0YcRUtHe
-"""
-
-import csv
-import os
-
-import datasets
-
-
-_CITATION = """\
-@article{article,
-author = {Salah, Ramzi and Zakaria, Lailatul},
-year = {2018},
-month = {12},
-pages = {},
-title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},
-volume = {96},
-journal = {Journal of Theoretical and Applied Information Technology}
-}
-"""
-
-_DESCRIPTION = """\
-Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.
-"""
-
-_HOMEPAGE = "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus"
-_HOMEPAGE = "https://github.com/omarmohamed2011/caner_data_copy"
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-
-#_URL = "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus/archive/master.zip"
-_URL  = 'https://github.com/omarmohamed2011/caner_data_copy/blob/main/df_caner.zip'
-
-class Caner(datasets.GeneratorBasedBuilder):
-    """Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities"""
-
-    VERSION = datasets.Version("1.1.0")
-
-    def _info(self):
-
-        features = datasets.Features(
-            {
-                "token": datasets.Value("string"),
-                "ner_tag": datasets.ClassLabel(
-                    names=[
-                        "Allah",
-                        "Book",
-                        "Clan",
-                        "Crime",
-                        "Date",
-                        "Day",
-                        "Hell",
-                        "Loc",
-                        "Meas",
-                        "Mon",
-                        "Month",
-                        "NatOb",
-                        "Number",
-                        "O",
-                        "Org",
-                        "Para",
-                        "Pers",
-                        "Prophet",
-                        "Rlig",
-                        "Sect",
-                        "Time",
-                    ]
-                ),
-            }
-        )
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        my_urls = _URL
-        data_dir = dl_manager.download_and_extract(my_urls)
-        
-        data_dir = '/content/df_caner.csv'
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-               
-                gen_kwargs={
-                    "filepath": data_dir,
-                    #os.path.join(   data_dir, "/df_caner.csv"),
-                    "split": "train",
-                },
-            )
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Yields examples."""
-
-        with open(filepath, encoding="utf-8") as csv_file:
-            reader = csv.reader(csv_file, delimiter=",")
-            next(reader, None)
-
-            for id_, row in enumerate(reader):
-
-                yield id_, {
-                    "token": row[0],
-                    "ner_tag": row[1],
-                }