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
op_num: int64
to
{}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, 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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 464, in __iter__
yield from self.ex_iterable
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 363, in __iter__
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 299, 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 128, 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 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
op_num: int64
to
{}
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.
Wiki2019-multilingual-dense-embeddings
Qdrant vector database containing dense embeddings for the wiki_composite collection, built from 2019 Wikipedia dumps across 8 languages.
Collection Details
| Property | Value |
|---|---|
| Embedding model | nvidia/llama-embed-nemotron-8b |
| Qdrant version | 1.17.0 |
| Vector size | 4096 |
| Distance metric | Cosine |
| Storage mode | On-disk (payload + vectors) |
| Total size | 947 GB (882 GiB) |
| Payload index | Keyword index on "wiki" field |
| Chunking strategy | Recursive Character Text Splitter |
| Chunk size | 512 tokens |
| Chunk overlap | 50 tokens |
Languages
| Code | Language |
|---|---|
arwiki |
Arabic |
bnwiki |
Bengali |
enwiki |
English |
fiwiki |
Finnish |
jawiki |
Japanese |
kowiki |
Korean |
ruwiki |
Russian |
tewiki |
Telugu |
Dense Embeddings Download Instructions
1. Download the storage directory
huggingface-cli download ronak-wani/Wiki2019-multilingual-dense-embeddings \
--repo-type dataset \
--local-dir ./Wiki2019-multilingual-dense-embeddings
2. Build the Qdrant sandbox (if not already built)
apptainer build --sandbox qdrant_sandbox docker://qdrant/qdrant:v1.17.0
3. Start Qdrant pointing at the restored storage
apptainer exec \
--bind ./Wiki2019-multilingual-dense-embeddings/storage:/qdrant/storage \
--env QDRANT__SERVICE__HOST=0.0.0.0 \
qdrant_sandbox qdrant_sandbox/qdrant/qdrant
4. Verify the collection is live
curl -s http://localhost:6333/collections/wiki_composite | python3 -m json.tool
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