The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
repo: string
source_rows: int64
kept_rows: int64
mode_parallel: int64
status: string
seconds: double
dropped_english_heavy: int64
mode_monolingual_text: int64
to
{'repo': Value('string'), 'source_rows': Value('int64'), 'kept_rows': Value('int64'), 'mode_monolingual_text': Value('int64'), 'dropped_english_heavy': Value('int64'), 'status': Value('string'), 'seconds': Value('float64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
repo: string
source_rows: int64
kept_rows: int64
mode_parallel: int64
status: string
seconds: double
dropped_english_heavy: int64
mode_monolingual_text: int64
to
{'repo': Value('string'), 'source_rows': Value('int64'), 'kept_rows': Value('int64'), 'mode_monolingual_text': Value('int64'), 'dropped_english_heavy': Value('int64'), 'status': Value('string'), 'seconds': Value('float64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Filtered African-language datasets
This repository contains non-destructive filtered derivatives of publicly accessible Hugging Face datasets relevant to Hausa, Nigerian languages, and selected African languages. The original repositories remain the authoritative sources and were not modified.
Scope and provenance
Each JSONL file preserves the source repository, source split, and source row index in _source_repo, _source_split, and _source_row_index. Per-repository counts and SHA-256 checksums are in manifest.json, with individual audit files under audit/.
The first publication wave contains 11 audited derivatives and 416,020 retained rows (397.3 MiB of JSONL). The candidate discovery and deferred-source catalog is maintained separately in the accompanying audit report.
Filtering rules
The transformation normalizes Unicode to NFC and collapses whitespace; removes null or empty text; removes exact duplicate normalized records; removes URLs, email addresses, bot/prompt-injection artifacts, and obvious social-spam patterns; removes only an allowlisted set of parenthetical English glosses; and removes English-heavy monolingual records using a conservative threshold of at least three unambiguous English prose words and an English-word ratio of at least 0.20. Bilingual and parallel corpora are not filtered by deleting their English side, because that would destroy alignment and translation utility. ASR/audio sources are catalogued separately unless a text-only derivative was safely produced.
License and responsible use
Every derivative must be used subject to the original source repository’s license, attribution requirements, dataset-card terms, and any additional restrictions. This repository does not change upstream copyrights or grant a blanket license. In particular, some corpora contain copyrighted source material or terms-of-use requirements even when the compilation carries a permissive license. Users must inspect the upstream card before redistribution or commercial use.
Validation
In addition to programmatic checks, independent random samples were inspected from the Hausa, Kanuri, and Nupe source datasets. The audit report records those checks and explains why bilingual and audio corpora use modality-aware rules.
Citation
When using a file, cite both this derivative repository and the corresponding upstream repository named in its _source_repo field. See manifest.json for the complete mapping.
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