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The dataset generation failed because of a cast error
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 6 new columns ({'f1', 'reasoning', 'label', 'index', 'pearson_correlation', 'density'}) and 2 missing columns ({'abstracts', 'doc_ids'}). This happened while the json dataset builder was generating data using hf://datasets/charlieoneill/saerchModels/astroPH_feature_analysis_results_64.json (at revision b2cbb184b58880b77a546511e11d8fd214c40556) 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 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast f1: double reasoning: string label: string index: int64 pearson_correlation: double density: double to {'doc_ids': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'abstracts': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)} 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 1577, 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 1191, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 6 new columns ({'f1', 'reasoning', 'label', 'index', 'pearson_correlation', 'density'}) and 2 missing columns ({'abstracts', 'doc_ids'}). This happened while the json dataset builder was generating data using hf://datasets/charlieoneill/saerchModels/astroPH_feature_analysis_results_64.json (at revision b2cbb184b58880b77a546511e11d8fd214c40556) 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)
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doc_ids
sequence | abstracts
sequence | index
int64 | pearson_correlation
float64 | reasoning
string | label
string | density
float64 | f1
float64 |
---|---|---|---|---|---|---|---|
["1607.01526","1607.03009","1607.06240","1607.07246","1607.07888","1607.08820","1607.06710","1607.08(...TRUNCATED) | ["'Globular clusters as tracers of the host galaxy mass distribution: the Fornax dSph test case'","'(...TRUNCATED) | null | null | null | null | null | null |
null | null | 2 | 0.66279 | "### Step 1: Identify Common Topics, Concepts, and Features in Max-Activating Examples\n\n1. **Stran(...TRUNCATED) | Strange quark matter and strange stars | 0.006939 | 0.75 |
null | null | 1 | 0.982008 | "### Step 1: Identify Potential Topics, Concepts, and Features\n\nBased on the max-activating exampl(...TRUNCATED) | Centaurs, TNOs, rings, satellites, characteristics | 0.002961 | 1 |
null | null | 4 | 0.510527 | "### Step 1: Identify Common Topics, Concepts, and Features in Max-Activating Examples\n\n1. **Impli(...TRUNCATED) | Implicit numerical methods | 0.001101 | 0.75 |
null | null | 0 | 0.724368 | "### Step 1: Identify Potential Topics, Concepts, and Features\n\nBased on the max-activating exampl(...TRUNCATED) | Triaxial models in astronomy | 0.003665 | 0.8 |
null | null | 3 | 0.967773 | "### Step 1: Identify Potential Topics, Concepts, and Features\n\nBased on the max-activating exampl(...TRUNCATED) | Cosmological observables in theoretical models | 0.006074 | 1 |
null | null | 8 | 0 | "### Step 1: Identify Potential Topics, Concepts, and Features\n\nBased on the max-activating exampl(...TRUNCATED) | Gravitational potential and energy | 0.003197 | 0.6 |
null | null | 7 | 0.186989 | "### Step 1: Identify Potential Topics, Concepts, and Features\n\nBased on the max-activating exampl(...TRUNCATED) | Barred galaxies and their dynamics | 0.004122 | 0.6 |
null | null | 6 | 0.683468 | "### Step 1: Identify Common Topics, Concepts, and Features in Max-Activating Examples\n\n1. **Comet(...TRUNCATED) | Comet C/1995 O1 (Hale-Bopp) | 0.001304 | 0.857143 |
null | null | 5 | 0.570447 | "### Step 1: Identify Potential Topics, Concepts, and Features\n\nBased on the max-activating exampl(...TRUNCATED) | Magnetic fields in β Cephei stars | 0.001042 | 0.75 |
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