Datasets:

---

Haoxuan1111

/

Modelcards-annotate

Like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'arxivId'}) and 1 missing columns ({'generated_model_card'}).

This happened while the json dataset builder was generating data using

hf://datasets/Haoxuan1111/Modelcards-annotate/sampled_model_id_arxiv_part1.json (at revision 44d6c2b5b0d41cdbb6da5974177d0c38d5e162b7)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              model_id: string
              arxivId: string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 323
              to
              {'model_id': Value('string'), 'generated_model_card': {'caveats_recommendations': {'deployment_recommendations': {'confidence': Value('string'), 'content': Value('string')}, 'known_limitations': {'confidence': Value('string'), 'content': Value('string')}, 'monitoring_requirements': {'confidence': Value('string'), 'content': Value('string')}, 'user_guidelines': {'confidence': Value('string'), 'content': Value('string')}}, 'ethical_considerations': {'consent': {'confidence': Value('string'), 'content': Value('string')}, 'cultural_appropriation': {'confidence': Value('string'), 'content': Value('string')}, 'dual_use_risks': {'confidence': Value('string'), 'content': Value('string')}, 'economic_impact': {'confidence': Value('string'), 'content': Value('string')}, 'environmental_impact': {'confidence': Value('string'), 'content': Value('string')}, 'intellectual_property': {'confidence': Value('string'), 'content': Value('string')}, 'misinformation': {'confidence': Value('string'), 'content': Value('string')}, 'privacy': {'confidence': Value('string'), 'content': Value('string')}}, 'generative_capabilities': {'consistency': {'confidence': Value('string'), 'content': Value('string')}, 'content_types': {'confidence': Value('string'), 'content': Value('string')}, 'customization': {'confidence': Value('string'), 'content': Value('string')}, 'generation_quality': {'confidence': Value('string'), 'content': Value('string')}, 'latency': {'confidence': Value('string'), 'content': Value('str
              ...
               {'confidence': Value('string'), 'content': Value('string')}, 'cultural_sensitivity': {'confidence': Value('string'), 'content': Value('string')}, 'factual_accuracy': {'confidence': Value('string'), 'content': Value('string')}, 'generation_quality_metrics': {'confidence': Value('string'), 'content': Value('string')}, 'robustness': {'confidence': Value('string'), 'content': Value('string')}, 'safety_metrics': {'confidence': Value('string'), 'content': Value('string')}}, 'safety_considerations': {'bias_analysis': {'confidence': Value('string'), 'content': Value('string')}, 'child_safety': {'confidence': Value('string'), 'content': Value('string')}, 'content_safety': {'confidence': Value('string'), 'content': Value('string')}, 'fairness_metrics': {'confidence': Value('string'), 'content': Value('string')}, 'jailbreaking_resistance': {'confidence': Value('string'), 'content': Value('string')}, 'red_team_testing': {'confidence': Value('string'), 'content': Value('string')}}, 'training_data': {'consent_privacy': {'confidence': Value('string'), 'content': Value('string')}, 'data_filtering': {'confidence': Value('string'), 'content': Value('string')}, 'demographic_representation': {'confidence': Value('string'), 'content': Value('string')}, 'evaluation_datasets': {'confidence': Value('string'), 'content': Value('string')}, 'language_coverage': {'confidence': Value('string'), 'content': Value('string')}, 'training_corpus': {'confidence': Value('string'), 'content': Value('string')}}}}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1456, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1055, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'arxivId'}) and 1 missing columns ({'generated_model_card'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/Haoxuan1111/Modelcards-annotate/sampled_model_id_arxiv_part1.json (at revision 44d6c2b5b0d41cdbb6da5974177d0c38d5e162b7)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)