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README.md

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----
-license: gfdl
-task_categories:
-- text-generation
-language:
-- hu
-pretty_name: tota_gep_arpad
-size_categories:
-- n<1K
----

default/test/0000.parquet

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default/train/0000.parquet

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default/validation/0000.parquet

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+size 68784

tota_gep_arpad.py

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-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""MIHVG TOTAWARPAD dataset."""
-
-import os
-import datasets
-
-_CITATION = """\
-@misc{
-  author={Laszlo, David},
-  title={totag-arpad},
-  year={2023},
-  howpublished={\\url{https://github.com/stedko/totagarpad}}
-}"""
-
-_DESCRIPTION = """\
-Train dataset Tota W. Arpad cikkei a hvg-rol \
-"""
-
-class TotaGArpad(datasets.GeneratorBasedBuilder):
-    """Tota Gep Arpad dataset builder."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({"text": datasets.Value("string")}),
-            supervised_keys=None,
-            homepage="https://github.com/stedko/totagarpad/blob/main/totawarpad-articles.txt",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        download_path = dl_manager.download_and_extract(
-            "https://raw.githubusercontent.com/stedko/totagarpad/main/totawarpad-articles.txt"
-        )
-        if os.path.isdir(download_path):
-            txt_path = os.path.join(download_path, "input.txt")
-        else:
-            txt_path = download_path
-        with open(txt_path, "r", encoding="utf-8") as f:
-            text = f.read()
-
-        i = int(len(text) * 0.9)
-        train_text, text = text[:i], text[i:]
-        i = int(len(text) * 0.5)
-        validation_text, text = text[:i], text[i:]
-        test_text = text
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"split_key": "train", "split_text": train_text},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"split_key": "validation", "split_text": validation_text},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"split_key": "test", "split_text": test_text},
-            ),
-        ]
-
-    def _generate_examples(self, split_key, split_text):
-        data_key = split_key 
-        feature_dict = {"text": split_text}
-        yield data_key, feature_dict