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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """\
Every prompt dataset.
Every Prompt is a data-driven approach to mining instructions from the web.
It contains over a million FAQs and HowTos from around the world in a structured format.
It also has basic pre-processing to calculate the length of the useful text and identify the language of that text with the help of GCLD3
"""
_URLS = [
"every_prompt.jsonlines",
]
class EveryPromptDataset(datasets.GeneratorBasedBuilder):
"""Every Prompt Dataset"""
VERSION = datasets.Version("1.0.0")
DEFAULT_CONFIG_NAME = "default"
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="default", version=VERSION, description=""),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"language": datasets.Value("string"),
"language_is_reliable": datasets.Value("bool"),
"text_length": datasets.Value("int32"),
"data_length": datasets.Value("int32"),
"text_to_data_ratio": datasets.Value("float32"),
"url": datasets.Value("string"),
"schema_type": datasets.Value("string"),
"payload": datasets.Value("string"),
}
),
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download(_URLS)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files}
)
]
def _generate_examples(self, filepaths):
"""This function returns the examples in the raw (text) form."""
logger.info("generating examples from = %s", filepaths)
key = 0
for path in filepaths:
with open(path, encoding="utf-8") as f:
for instruction_str in f:
instruction = json.loads(instruction_str)
yield key, instruction
key += 1
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