t5-base-dutch / streaming_dataset_filter_test.py
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Saving weights and logs of step 1500
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from clean import clean_text
from datasets import load_dataset
dataset_v0 = load_dataset('oscar', "unshuffled_deduplicated_nl", split='train', streaming=True)
def f(obj):
obj["text"] = clean_text(obj["text"])
return obj
dataset_v1 = dataset_v0.map(f)
dataset_v2 = dataset_v1.filter(lambda obj: obj['text'] is not None)
it = iter(dataset_v0)
print(next(it))
print(next(it))
print(next(it))
it = iter(dataset_v1)
print(next(it))
print(next(it))
print(next(it))
it = iter(dataset_v2)
print(next(it))
print(next(it))
print(next(it))