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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 |
|---|---|
devanagari-digit-recognition-using-quantum | 2,506.09069 |
devbench-a-comprehensive-benchmark-for | 2,403.08604 |
devbench-a-multimodal-developmental-benchmark | 2,406.10215 |
devbots-can-co-design-apis | 2,312.05733 |
devdan-deep-evolving-denoising-autoencoder | 1,910.04062 |
develop-end-to-end-anomaly-detection-system | 2,402.10085 |
develop-machine-learning-based-predictive | 1,806.11369 |
developability-approximation-for-neural | 2,308.039 |
developement-of-reinforcement-learning-based | 2,411.09499 |
developer-perspectives-on-licensing-and | 2,411.10877 |
developers-leverage-capital-market-financing | 2,312.05013 |
developing-a-cardiovascular-disease-risk | 1,611.0902 |
developing-a-climate-litigation-framework | 2,502.03906 |
developing-a-component-comment-extractor-from | 2,207.05979 |
developing-a-comprehensive-framework-for | 1,702.06151 |
developing-a-compressed-object-detection | 2,108.00392 |
developing-a-concept-level-knowledge-base-for | 1,707.04408 |
developing-a-conversational-recommendation | 2,104.06552 |
developing-a-data-analysis-pipeline-for | 2,201.06074 |
developing-a-dataset-adaptive-normalized | 2,412.07244 |
developing-a-dual-stage-vision-transformer | 2,409.18257 |
developing-a-fair-individualized-polysocial | 2,309.02467 |
developing-a-fidelity-evaluation-approach-for | 2,106.08492 |
developing-a-fine-grained-corpus-for-a-less-1 | 1,909.11467 |
developing-a-foundation-of-vector-symbolic | 2,501.05368 |
developing-a-framework-for-auditing-large | 2,402.09346 |
developing-a-framework-to-support-human | 2,505.03053 |
developing-a-free-and-open-source-automated | 2,206.09742 |
developing-a-gender-classification-approach | 2,001.10966 |
developing-a-general-purpose-clinical | 2,210.06566 |
developing-a-high-performance-framework-for | 2,506.1093 |
developing-a-hybrid-data-driven-mechanistic | 2,002.02737 |
developing-a-knowledge-graph-framework-for | 2,209.1195 |
developing-a-machine-learning-algorithm-based | 2,111.09496 |
developing-a-machine-learning-algorithm-to | 2,201.12384 |
developing-a-machine-learning-based-clinical | 2,308.10372 |
developing-a-machine-learning-framework-for | 1,804.09046 |
developing-a-meta-suggestion-engine-for | 2,110.12594 |
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 |
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 |
End of preview.
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