Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
premise: string
hypothesis: string
label: int64
example_id: string
is_valid: bool
version: string
compliance: struct<babylm_track: string, english_word_limit: string, sanskrit_outside_budget: bool, notes: strin (... 2 chars omitted)
child 0, babylm_track: string
child 1, english_word_limit: string
child 2, sanskrit_outside_budget: bool
child 3, notes: string
corpora: struct<english_100m: struct<description: string, license: string, text_path: string, binary_path: st (... 690 chars omitted)
child 0, english_100m: struct<description: string, license: string, text_path: string, binary_path: string, status: string, (... 182 chars omitted)
child 0, description: string
child 1, license: string
child 2, text_path: string
child 3, binary_path: string
child 4, status: string
child 5, source: string
child 6, budget: string
child 7, components: list<item: struct<name: string, estimated_tokens: string, license: string>>
child 0, item: struct<name: string, estimated_tokens: string, license: string>
child 0, name: string
child 1, estimated_tokens: string
child 2, license: string
child 8, word_count: int64
child 9, token_count: int64
child 10, file_size_mb: double
child 1, dose_grammar: struct<description: string, license: string, text_path: string, binary_path: string, status: string, (... 370 chars omitted)
child 0, description: string
child 1, license: string
child 2, text_path: string
child 3, binary_path: string
child 4, status: string
child 5, source: string
child 6, notes: string
child 7, generation_params: struct<dhatus_sampled: int64, lakaras: int64, purusha_forms: int64, vacana_forms: int64, total_combi (... 25 chars omitted)
child 0, dhatus_sampled: int64
child 1, lakaras: int64
child 2, purusha_forms: int64
child 3, vacana_forms: int64
child 4, total_combinations_attempted: int64
child 8, word_count: int64
child 9, token_count: int64
child 10, file_size_mb: double
child 11, samples: list<item: struct<form: string, dhatu: string, lakara: string, purusha: string, vacana: string, deri (... 21 chars omitted)
child 0, item: struct<form: string, dhatu: string, lakara: string, purusha: string, vacana: string, derivation_step (... 9 chars omitted)
child 0, form: string
child 1, dhatu: string
child 2, lakara: string
child 3, purusha: string
child 4, vacana: string
child 5, derivation_steps: int64
tokenizer: struct<path: string, type: string, vocab_size: int64, encoding: string>
child 0, path: string
child 1, type: string
child 2, vocab_size: int64
child 3, encoding: string
generated_at: string
to
{'generated_at': Value('string'), 'version': Value('string'), 'corpora': {'english_100m': {'description': Value('string'), 'license': Value('string'), 'text_path': Value('string'), 'binary_path': Value('string'), 'status': Value('string'), 'source': Value('string'), 'budget': Value('string'), 'components': List({'name': Value('string'), 'estimated_tokens': Value('string'), 'license': Value('string')}), 'word_count': Value('int64'), 'token_count': Value('int64'), 'file_size_mb': Value('float64')}, 'dose_grammar': {'description': Value('string'), 'license': Value('string'), 'text_path': Value('string'), 'binary_path': Value('string'), 'status': Value('string'), 'source': Value('string'), 'notes': Value('string'), 'generation_params': {'dhatus_sampled': Value('int64'), 'lakaras': Value('int64'), 'purusha_forms': Value('int64'), 'vacana_forms': Value('int64'), 'total_combinations_attempted': Value('int64')}, 'word_count': Value('int64'), 'token_count': Value('int64'), 'file_size_mb': Value('float64'), 'samples': List({'form': Value('string'), 'dhatu': Value('string'), 'lakara': Value('string'), 'purusha': Value('string'), 'vacana': Value('string'), 'derivation_steps': Value('int64')})}}, 'tokenizer': {'path': Value('string'), 'type': Value('string'), 'vocab_size': Value('int64'), 'encoding': Value('string')}, 'compliance': {'babylm_track': Value('string'), 'english_word_limit': Value('string'), 'sanskrit_outside_budget': Value('bool'), 'notes': Value('string')}}
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(
^^^^^^^^^
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 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
premise: string
hypothesis: string
label: int64
example_id: string
is_valid: bool
version: string
compliance: struct<babylm_track: string, english_word_limit: string, sanskrit_outside_budget: bool, notes: strin (... 2 chars omitted)
child 0, babylm_track: string
child 1, english_word_limit: string
child 2, sanskrit_outside_budget: bool
child 3, notes: string
corpora: struct<english_100m: struct<description: string, license: string, text_path: string, binary_path: st (... 690 chars omitted)
child 0, english_100m: struct<description: string, license: string, text_path: string, binary_path: string, status: string, (... 182 chars omitted)
child 0, description: string
child 1, license: string
child 2, text_path: string
child 3, binary_path: string
child 4, status: string
child 5, source: string
child 6, budget: string
child 7, components: list<item: struct<name: string, estimated_tokens: string, license: string>>
child 0, item: struct<name: string, estimated_tokens: string, license: string>
child 0, name: string
child 1, estimated_tokens: string
child 2, license: string
child 8, word_count: int64
child 9, token_count: int64
child 10, file_size_mb: double
child 1, dose_grammar: struct<description: string, license: string, text_path: string, binary_path: string, status: string, (... 370 chars omitted)
child 0, description: string
child 1, license: string
child 2, text_path: string
child 3, binary_path: string
child 4, status: string
child 5, source: string
child 6, notes: string
child 7, generation_params: struct<dhatus_sampled: int64, lakaras: int64, purusha_forms: int64, vacana_forms: int64, total_combi (... 25 chars omitted)
child 0, dhatus_sampled: int64
child 1, lakaras: int64
child 2, purusha_forms: int64
child 3, vacana_forms: int64
child 4, total_combinations_attempted: int64
child 8, word_count: int64
child 9, token_count: int64
child 10, file_size_mb: double
child 11, samples: list<item: struct<form: string, dhatu: string, lakara: string, purusha: string, vacana: string, deri (... 21 chars omitted)
child 0, item: struct<form: string, dhatu: string, lakara: string, purusha: string, vacana: string, derivation_step (... 9 chars omitted)
child 0, form: string
child 1, dhatu: string
child 2, lakara: string
child 3, purusha: string
child 4, vacana: string
child 5, derivation_steps: int64
tokenizer: struct<path: string, type: string, vocab_size: int64, encoding: string>
child 0, path: string
child 1, type: string
child 2, vocab_size: int64
child 3, encoding: string
generated_at: string
to
{'generated_at': Value('string'), 'version': Value('string'), 'corpora': {'english_100m': {'description': Value('string'), 'license': Value('string'), 'text_path': Value('string'), 'binary_path': Value('string'), 'status': Value('string'), 'source': Value('string'), 'budget': Value('string'), 'components': List({'name': Value('string'), 'estimated_tokens': Value('string'), 'license': Value('string')}), 'word_count': Value('int64'), 'token_count': Value('int64'), 'file_size_mb': Value('float64')}, 'dose_grammar': {'description': Value('string'), 'license': Value('string'), 'text_path': Value('string'), 'binary_path': Value('string'), 'status': Value('string'), 'source': Value('string'), 'notes': Value('string'), 'generation_params': {'dhatus_sampled': Value('int64'), 'lakaras': Value('int64'), 'purusha_forms': Value('int64'), 'vacana_forms': Value('int64'), 'total_combinations_attempted': Value('int64')}, 'word_count': Value('int64'), 'token_count': Value('int64'), 'file_size_mb': Value('float64'), 'samples': List({'form': Value('string'), 'dhatu': Value('string'), 'lakara': Value('string'), 'purusha': Value('string'), 'vacana': Value('string'), 'derivation_steps': Value('int64')})}}, 'tokenizer': {'path': Value('string'), 'type': Value('string'), 'vocab_size': Value('int64'), 'encoding': Value('string')}, 'compliance': {'babylm_track': Value('string'), 'english_word_limit': Value('string'), 'sanskrit_outside_budget': Value('bool'), 'notes': Value('string')}}
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.
Prabhāsa grammar/reasoning data (BabyLM 2026)
Synthetic Pāṇinian morphology corpus + Navya-Nyāya inference examples used by the Prabhāsa mechanisms (kāraka masking, śābdabodha objective). Files: paninian_v1.jsonl (Pāṇinian forms), pramana_examples.jsonl (Pañcāvayava chains), nli_examples.jsonl. See github.com/SharathSPhD/prabhasa-babylm.
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