newstext.py

import datasets
import os
from datasets import DatasetBuilder, SplitGenerator, DownloadConfig, Split

from datasets import GeneratorBasedBuilder, SplitGenerator, Split

class TextDataset(GeneratorBasedBuilder):
    VERSION = "1.0.0"
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="text", version=VERSION, description="Text data"),
    ]
    
    def _info(self):
        return datasets.DatasetInfo(features=datasets.Features({'text': datasets.Value('string')}))
        
    def _split_generators(self, dl_manager):
        
        train_path = "./train/new_format_data.txt"
        val_path = "./val/new_format_data_val_removedup.txt"
        train_path = dl_manager.download_and_extract(train_path)
        val_path = dl_manager.download_and_extract(val_path)
        return [
            SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": train_path}),
            SplitGenerator(name=Split.VALIDATION, gen_kwargs={"filepath": val_path}),
        ]
    
    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as f:
            for id_, line in enumerate(f):
                yield id_, {"text": line.strip()}