Datasets:
Languages:
Telugu
Multilinguality:
monolingual
Size Categories:
n<1K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
File size: 3,602 Bytes
21cefab 67c69f7 21cefab c114b61 21cefab |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 |
# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Telugu Books Dataset"""
import csv
import os
import datasets
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {Indic NLP - Natural Language Processing for Indian Languages},
authors = {Sudalai Rajkumar, Anusha Motamarri},
year={2019}
}
"""
_DESCRIPTION = """\
This dataset is created by scraping telugu novels from teluguone.com this dataset can be used for nlp tasks like topic modeling, word embeddings, transfer learning etc
"""
_HOMEPAGE = "https://www.kaggle.com/sudalairajkumar/telugu-nlp"
_LICENSE = "Data files © Original Authors"
_FILENAME = "telugu_books.csv"
class TeluguBooks(datasets.GeneratorBasedBuilder):
"""Telugu novels"""
VERSION = datasets.Version("1.1.0")
@property
def manual_download_instructions(self):
return """\
You need to go to https://www.kaggle.com/sudalairajkumar/telugu-nlp,
and manually download the telugu_books. Once it is completed,
a file named telugu_books.zip will be appeared in your Downloads folder
or whichever folder your browser chooses to save files to. You then have
to unzip the file and move telugu_books,csv under <path/to/folder>.
The <path/to/folder> can e.g. be "~/manual_data".
telugu_books can then be loaded using the following command `datasets.load_dataset("telugu_books", data_dir="<path/to/folder>")`.
"""
def _info(self):
features = datasets.Features(
{
"text": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
if not os.path.exists(path_to_manual_file):
raise FileNotFoundError(
f"{path_to_manual_file} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('telugu_books', data_dir=...)` that includes file name {_FILENAME}. Manual download instructions: {self.manual_download_instructions}"
)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepath": os.path.join(path_to_manual_file, "telugu_books.csv"),
"split": "train",
},
),
]
def _generate_examples(self, filepath, split):
"""Yields examples."""
with open(filepath, encoding="utf-8") as csv_file:
csv_reader = csv.reader(csv_file)
for id_, row in enumerate(csv_reader):
_, text = row
yield id_, {"text": text}
|