Datasets:

xzz789
/

llava_instruct_150k_formal_1008

Tasks:

Image-to-Text

Size:

n<1K

Tags:

multimodal

sft

License:

Dataset card Files Files and versions

xet

Community

Dataset Viewer

Duplicate

Split (1)

train

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
_data_files: list<item: struct<filename: string>>
  child 0, item: struct<filename: string>
      child 0, filename: string
_fingerprint: string
_format_columns: null
_format_kwargs: struct<>
_format_type: null
_output_all_columns: bool
_split: string
selection_method: string
selected_row_count: int64
features: struct<completion: struct<_type: string, dtype: string>, image: struct<_type: string>, prompt: struc (... 32 chars omitted)
  child 0, completion: struct<_type: string, dtype: string>
      child 0, _type: string
      child 1, dtype: string
  child 1, image: struct<_type: string>
      child 0, _type: string
  child 2, prompt: struct<_type: string, dtype: string>
      child 0, _type: string
      child 1, dtype: string
source_row_count: int64
dataset: string
selected_source_indices_in_output_order: list<item: int64>
  child 0, item: int64
source_path: string
selection_sha256: string
pool_note: string
seed: int64
to
{'dataset': Value('string'), 'features': {'completion': {'_type': Value('string'), 'dtype': Value('string')}, 'image': {'_type': Value('string')}, 'prompt': {'_type': Value('string'), 'dtype': Value('string')}}, 'pool_note': Value('string'), 'seed': Value('int64'), 'selected_row_count': Value('int64'), 'selected_source_indices_in_output_order': List(Value('int64')), 'selection_method': Value('string'), 'selection_sha256': Value('string'), 'source_path': Value('string'), 'source_row_count': Value('int64')}
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
              _data_files: list<item: struct<filename: string>>
                child 0, item: struct<filename: string>
                    child 0, filename: string
              _fingerprint: string
              _format_columns: null
              _format_kwargs: struct<>
              _format_type: null
              _output_all_columns: bool
              _split: string
              selection_method: string
              selected_row_count: int64
              features: struct<completion: struct<_type: string, dtype: string>, image: struct<_type: string>, prompt: struc (... 32 chars omitted)
                child 0, completion: struct<_type: string, dtype: string>
                    child 0, _type: string
                    child 1, dtype: string
                child 1, image: struct<_type: string>
                    child 0, _type: string
                child 2, prompt: struct<_type: string, dtype: string>
                    child 0, _type: string
                    child 1, dtype: string
              source_row_count: int64
              dataset: string
              selected_source_indices_in_output_order: list<item: int64>
                child 0, item: int64
              source_path: string
              selection_sha256: string
              pool_note: string
              seed: int64
              to
              {'dataset': Value('string'), 'features': {'completion': {'_type': Value('string'), 'dtype': Value('string')}, 'image': {'_type': Value('string')}, 'prompt': {'_type': Value('string'), 'dtype': Value('string')}}, 'pool_note': Value('string'), 'seed': Value('int64'), 'selected_row_count': Value('int64'), 'selected_source_indices_in_output_order': List(Value('int64')), 'selection_method': Value('string'), 'selection_sha256': Value('string'), 'source_path': Value('string'), 'source_row_count': Value('int64')}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

LLaVA auxiliary subset (1008 rows)

This repository contains the deterministic Understanding-auxiliary view used by the current four-family umm-sft paired_ug_formal recipes.

Rows published: 1,008
Historical bounded source pool: 16,000 rows
Verified rz6000 replica used to reconstruct that pool: 100,547 rows
Pool construction: first 16,000 rows of the verified row-ordered builder output
Selection seed: 178430
Selection details: formal_selection_receipt.json
Features: prompt, image, completion

Only the 1,008 rows consumed by the formal source contract are published; the 100,547-row replica is not. The source metadata did not declare a license; other is only a metadata placeholder, and users must follow the original source terms.

Restore it as an exact datasets.save_to_disk directory after downloading the repository files:

from datasets import load_from_disk
dataset = load_from_disk("/path/to/checked-out-repository")

Downloads last month: 58

Total file size:

449 MB