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import datasets
features = datasets.Features(
{
"source": datasets.Value(dtype="string", id=None),
"id": datasets.Value(dtype="string", id=None),
"text": datasets.Value(dtype="string", id=None),
"added": datasets.Value(dtype="string", id=None),
"timestamp": datasets.Value(dtype="timestamp[s]", id=None),
"metadata": {"url": datasets.Value(dtype="string", id=None)},
}
)
dataset = datasets.load_dataset(
"json",
data_files={
"train": "fi_processed/c4-fi.*.json",
"validation": "fi_processed/c4-fi-validation*.json",
},
features=features,
cache_dir="/researchdisk/datasets_cache",
num_proc=96,
)
dataset = dataset.flatten()
dataset = dataset.rename_column("metadata.url", "url")
dataset = dataset.remove_columns(["source", "id", "added"])
print(dataset)
dataset.save_to_disk("/researchdisk/mc4_3.1.0_fi", num_proc=96)
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