Datasets:

DDDDD-433
/

open-model-registry

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
variant_id: string
family: string
source_model_id: string
category: string
total_parameters_b: double
format: string
bits_per_weight: double
memory_estimate_gb: double
memory_estimate_basis: string
fit_status: string
license: string
license_status: string
official_checkpoint: bool
runtime_support: list<item: string>
  child 0, item: string
source_url: string
last_verified: timestamp[s]
notes: string
parameter_scope: string
discovered_at: timestamp[s]
candidates: list<item: struct<model_id: string, model_url: string, category_guess: string, parameters_total_b: d (... 213 chars omitted)
  child 0, item: struct<model_id: string, model_url: string, category_guess: string, parameters_total_b: double, lice (... 201 chars omitted)
      child 0, model_id: string
      child 1, model_url: string
      child 2, category_guess: string
      child 3, parameters_total_b: double
      child 4, license: string
      child 5, pipeline_tag: string
      child 6, downloads: int64
      child 7, likes: int64
      child 8, official_namespace: string
      child 9, tags: list<item: string>
          child 0, item: string
      child 10, discovered_at: timestamp[s]
      child 11, review_status: string
      child 12, reasons: list<item: string>
          child 0, item: string
to
{'discovered_at': Value('timestamp[s]'), 'candidates': List({'model_id': Value('string'), 'model_url': Value('string'), 'category_guess': Value('string'), 'parameters_total_b': Value('float64'), 'license': Value('string'), 'pipeline_tag': Value('string'), 'downloads': Value('int64'), 'likes': Value('int64'), 'official_namespace': Value('string'), 'tags': List(Value('string')), 'discovered_at': Value('timestamp[s]'), 'review_status': Value('string'), 'reasons': List(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(
                      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 478, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              variant_id: string
              family: string
              source_model_id: string
              category: string
              total_parameters_b: double
              format: string
              bits_per_weight: double
              memory_estimate_gb: double
              memory_estimate_basis: string
              fit_status: string
              license: string
              license_status: string
              official_checkpoint: bool
              runtime_support: list<item: string>
                child 0, item: string
              source_url: string
              last_verified: timestamp[s]
              notes: string
              parameter_scope: string
              discovered_at: timestamp[s]
              candidates: list<item: struct<model_id: string, model_url: string, category_guess: string, parameters_total_b: d (... 213 chars omitted)
                child 0, item: struct<model_id: string, model_url: string, category_guess: string, parameters_total_b: double, lice (... 201 chars omitted)
                    child 0, model_id: string
                    child 1, model_url: string
                    child 2, category_guess: string
                    child 3, parameters_total_b: double
                    child 4, license: string
                    child 5, pipeline_tag: string
                    child 6, downloads: int64
                    child 7, likes: int64
                    child 8, official_namespace: string
                    child 9, tags: list<item: string>
                        child 0, item: string
                    child 10, discovered_at: timestamp[s]
                    child 11, review_status: string
                    child 12, reasons: list<item: string>
                        child 0, item: string
              to
              {'discovered_at': Value('timestamp[s]'), 'candidates': List({'model_id': Value('string'), 'model_url': Value('string'), 'category_guess': Value('string'), 'parameters_total_b': Value('float64'), 'license': Value('string'), 'pipeline_tag': Value('string'), 'downloads': Value('int64'), 'likes': Value('int64'), 'official_namespace': Value('string'), 'tags': List(Value('string')), 'discovered_at': Value('timestamp[s]'), 'review_status': Value('string'), 'reasons': List(Value('string'))})}
              because column names don't match

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Open Model Registry

Machine-readable mirror of the GitHub registry for open and open-weight models targeting strict sub-12B inclusion and practical 16GB edge deployment.

The data/models.jsonl file contains primary model records. The data/deployment_variants.jsonl file contains official packed and quantized deployment records, including explicitly labeled over-limit edge exceptions. Memory values are estimates unless the record says they are measured or based on an official card.

This dataset is synchronized from https://github.com/DDDD-433/open-model-registry and should be treated as a published data mirror, not as a model-weight repository.

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