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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
model: string
embed_dim: int64
max_seq_length: int64
n_rows: int64
n_truncated: int64
scholars: struct<Ibn Baz: int64, Ibn Uthaymeen: int64, Al-Lajnah Ad-Daimah: int64, Saleh Al-Fawzan: int64, Abd (... 80 chars omitted)
child 0, Ibn Baz: int64
child 1, Ibn Uthaymeen: int64
child 2, Al-Lajnah Ad-Daimah: int64
child 3, Saleh Al-Fawzan: int64
child 4, Abdullah al-Manee: int64
child 5, Abdulaziz Aal ash-Sheikh: int64
child 6, Saleh bin Humaid: int64
generated_at_utc: string
source: string
to
{'model': Value('string'), 'embed_dim': Value('int64'), 'max_seq_length': Value('int64'), 'n_rows': Value('int64'), 'n_truncated': Value('int64'), 'source': Value('string'), 'generated_at_utc': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
model: string
embed_dim: int64
max_seq_length: int64
n_rows: int64
n_truncated: int64
scholars: struct<Ibn Baz: int64, Ibn Uthaymeen: int64, Al-Lajnah Ad-Daimah: int64, Saleh Al-Fawzan: int64, Abd (... 80 chars omitted)
child 0, Ibn Baz: int64
child 1, Ibn Uthaymeen: int64
child 2, Al-Lajnah Ad-Daimah: int64
child 3, Saleh Al-Fawzan: int64
child 4, Abdullah al-Manee: int64
child 5, Abdulaziz Aal ash-Sheikh: int64
child 6, Saleh bin Humaid: int64
generated_at_utc: string
source: string
to
{'model': Value('string'), 'embed_dim': Value('int64'), 'max_seq_length': Value('int64'), 'n_rows': Value('int64'), 'n_truncated': Value('int64'), 'source': Value('string'), 'generated_at_utc': 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.
Ibn Baz fatwas + Qwen3-Embedding-0.6B embeddings
19,727 fatwas of Sheikh Abdul Aziz ibn Baz (cleaned), with precomputed embeddings for semantic search. These are the data files used by the BinBaz-RAG app, which downloads them automatically on first run.
Files
| File | Description |
|---|---|
binbaz_clean.csv |
Cleaned corpus, one row per fatwa. |
qwen3_06b_title_answer_embeddings.pt |
PyTorch tensor, shape (19727, 1024), saved from Qwen/Qwen3-Embedding-0.6B. |
embedding_metadata.json |
Provenance: model, dimension, max sequence length, row counts, generation time. |
Row i of the .pt tensor is the embedding of row i of the CSV (fatwa_id equals the row index).
CSV columns
fatwa_id, source, question, answer, title, links, categories, embed_text, embed_token_count, truncated
source: scholar attribution (Ibn Baz), so other scholars can be merged in later.links: URL of the original fatwa on binbaz.org.sa.categories: stringified list of category tags (215 distinct tags).embed_text: the text that was embedded,title + " — " + answer.embed_token_count/truncated: Qwen3 token count ofembed_text, and whether it exceeds 1024 tokens.
How the embeddings were built
- Model:
Qwen/Qwen3-Embedding-0.6Bvia sentence-transformers,max_seq_length = 1024. - Input:
embed_text = title + " — " + answer, with no chunking. 864 rows (4.4%) are longer than 1024 tokens and are truncated for embedding only; the fullanswerstays intact in the CSV. - Documents are encoded without a prompt and the vectors are saved as produced, not L2-normalized. Normalize after loading before using cosine similarity (the app does).
- Cleaning: encoding repair (
charset_normalizer,ftfy), NFKC normalization, removal of scraping artifacts. No stemming, stopword removal or diacritic stripping.
Generated by notebook 01 on Kaggle (2x T4), 2026-09-08.
Source and license
The text comes from binbaz.org.sa, via the Kaggle dataset a5medashraf/bin-baz-fatwas-dataset (main source: Alsarmad/binbaz_database, MIT). Kaggle lists that dataset's license as "Other (specified in description)" with no further terms stated. This repository is released under MIT to match the upstream scraper, but the fatwa content belongs to its original publisher: please attribute binbaz.org.sa and link back to the original fatwa.
This is a research and search resource, not a fatwa authority.
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