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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    FileNotFoundError
Message:      [Errno 2] No such file or directory: ''
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/responses/", line 337, in get_first_rows_response
                  rows = get_rows(dataset, config, split, streaming=True, rows_max_number=rows_max_number, hf_token=hf_token)
                File "/src/services/worker/src/worker/", line 123, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/responses/", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/", line 718, in __iter__
                  for key, example in self._iter():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/", line 708, in _iter
                  yield from ex_iterable
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/", line 112, in __iter__
                  yield from self.generate_examples_fn(**self.kwargs)
                File "/tmp/modules-cache/datasets_modules/datasets/imthanhlv--binhvq_dedup/60d03216e35c1b592ca70ae909d1c1f504292e38e9622d04108a14fe9c34868e/", line 78, in _generate_examples
                  for doc in reader.read_jsonl_zst(filepath):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/lm_dataformat/", line 245, in read_jsonl_zst
                  with open(file, 'rb') as fh:
              FileNotFoundError: [Errno 2] No such file or directory: ''

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BinhVQ dedup

Important: Please install lm_dataformat by pip install lm_dataformat before using this dataset

How to use

import datasets

dataset = datasets.load_dataset("imthanhlv/binhvq_dedup")

Dataset information

This dataset was created from dump with date 21/05/2021. I applied some simple preprocessing:

  • Using BeautifulSoup to clean content
  • Each record is concatenate of (title + "\n" + sapo + "\n" + content)
  • Then perform shuffling + split train & validation + deduplicate (exact match using sha256)
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