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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 2 new columns ({'2310.01627', 'val-interactive-task-learning-with-gpt-dialog'}) and 2 missing columns ({'2207.05132', 'dev2vec-representing-domain-expertise-of'}).
This happened while the csv dataset builder was generating data using
hf://datasets/pwc-archive/pwc-paper-redirects/split/val.csv (at revision df2b4c2c8b0ddf85a585e453da4d3af10463f0e8)
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
val-interactive-task-learning-with-gpt-dialog: string
2310.01627: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 572
to
{'dev2vec-representing-domain-expertise-of': Value('string'), '2207.05132': Value('float64')}
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 1339, 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 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/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 2 new columns ({'2310.01627', 'val-interactive-task-learning-with-gpt-dialog'}) and 2 missing columns ({'2207.05132', 'dev2vec-representing-domain-expertise-of'}).
This happened while the csv dataset builder was generating data using
hf://datasets/pwc-archive/pwc-paper-redirects/split/val.csv (at revision df2b4c2c8b0ddf85a585e453da4d3af10463f0e8)
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)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.
dev2vec-representing-domain-expertise-of
string | 2207.05132
float64 |
|---|---|
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developing-a-general-purpose-clinical
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developing-a-hybrid-data-driven-mechanistic
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developing-a-knowledge-graph-framework-for
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developing-a-machine-learning-algorithm-based
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developing-a-machine-learning-algorithm-to
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developing-a-machine-learning-based-clinical
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developing-a-machine-learning-framework-for
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developing-a-meta-suggestion-engine-for
| 2,110.12594
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developing-a-modular-compiler-for-a-subset-of
| 2,501.04503
|
developing-a-multi-agent-and-self-adaptive
| 2,402.00515
|
developing-a-multi-variate-prediction-model-1
| 2,402.07619
|
developing-a-multi-variate-prediction-model
| 2,209.03727
|
developing-a-multilingual-annotated-corpus-of
| 2,003.07428
|
developing-a-named-entity-recognition-dataset
| 2,311.07161
|
developing-a-natural-language-understanding
| 2,310.09166
|
developing-a-new-autism-diagnosis-process
| 2,104.01137
|
developing-a-new-biophysical-tool-to-combine
| 1,506.06913
|
developing-a-novel-approach-for-periapical
| 2,111.07156
|
developing-a-novel-fair-loan-predictor
| 2,110.08944
|
developing-a-novel-image-marker-to-predict
| 2,309.07087
|
developing-a-pet-ct-foundation-model-for
| 2,503.02824
|
developing-a-philosophical-framework-for-fair
| 2,208.06308
|
developing-a-portable-natural-language
| 1,807.06638
|
developing-a-pragmatic-benchmark-for
| 2,410.08731
|
developing-a-production-system-for-purpose-of
| 2,205.06904
|
developing-a-purely-visual-based-obstacle
| 1,809.01268
|
developing-a-ranking-problem-library-rplib
| 2,206.11258
|
developing-a-real-estate-yield-investment
| 2,008.02629
|
developing-a-recommendation-benchmark-for
| 2,003.07336
|
developing-a-reliable-general-purpose
| 2,407.15441
|
developing-a-resource-constraint-edgeai-model
| 2,401.05355
|
developing-a-scalable-benchmark-for-assessing
| 2,308.16622
|
developing-a-series-of-ai-challenges-for-the
| 2,207.07033
|
developing-a-statistically-powerful-measure
| 1,608.04761
|
developing-a-successful-bomberman-agent
| 2,203.09608
|
developing-a-thailand-solar-irradiance-map
| 2,409.1632
|
developing-a-trusted-human-ai-network-for
| 2,112.11191
|
developing-a-tutoring-dialog-dataset-to
| 2,410.19231
|
developing-acoustic-models-for-automatic
| 2,404.16547
|
developing-all-skyrmion-spiking-neural
| 1,705.02995
|
developing-an-ai-based-integrated-system-for
| 2,401.09988
|
developing-an-ai-enabled-iiot-platform
| 2,207.04515
|
developing-an-algorithm-selector-for-green
| 2,409.08641
|
developing-an-anfis-pso-model-to-estimate
| 1,910.05118
|
developing-an-app-to-interpret-chest-x-rays
| 1,906.11282
|
developing-an-artificial-intelligence-tool
| 2,502.15698
|
developing-an-attention-based-ensemble
| 2,404.08935
|
developing-an-effective-training-dataset-to
| 2,411.08375
|
developing-an-efficient-corpus-using-ensemble
| 2,406.00789
|
developing-an-emotion-affective-open-domain
| 2,208.04565
|
developing-an-end-to-end-framework-for
| 2,409.00158
|
developing-an-explainable-artificial
| 2,409.05918
|
developing-an-icu-scoring-system-with
| 1,604.0673
|
developing-an-informal-formal-persian-corpus
| 2,308.05336
|
developing-an-nlp-based-recommender-system
| 2,207.0636
|
developing-an-ontology-for-ai-act-fundamental
| 2,501.10391
|
developing-an-ontology-for-the-access-to-the
| 1,702.04584
|
developing-an-openai-gym-compatible-framework
| 2,101.04434
|
developing-an-optimal-model-for-predicting
| 2,402.10492
|
developing-analyzing-and-evaluating-self
| 2,409.03114
|
developing-and-analyzing-boundary-detection
| 1,304.3447
|
developing-and-building-ontologies-in-cyber
| 2,306.00377
|
developing-and-defeating-adversarial-examples
| 2,008.10106
|
developing-and-deploying-deep-learning-models
| 2,301.01241
|
developing-and-deploying-industry-standards
| 2,403.14689
|
developing-and-deploying-machine-learning
| 2,004.07965
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developing-and-evaluating-a-design-method-for
| 2,402.01499
|
developing-and-evaluating-an-ai-assisted
| 2,503.09927
|
developing-and-evaluating-tiny-to-medium
| 2,307.14134
|
developing-and-improving-risk-models-using
| 2,009.04559
|
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