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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ValueError
Message: Not able to read records in the JSON file at hf://datasets/jieyuz2/WRENCH@d1185f6cfba8d5ace2a39229799cb3f1c136bf66/classification/Bioresponse/train.json. You should probably indicate the field of the JSON file containing your records. 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'2883', '2884', '2885', '2886', '2887', '2888', '2889', '2890', '2891', '2892', '2893', '2894', '2895', '2896', '2897', '2898', '2899', '2900', '2901', '2902', '2903', '2904', '2905', '2906', '2907', '2908', '2909', '2910', '2911', '2912', '2913', '2914', '2915', '2916', '2917', '2918', '2919', '2920', '2921', '2922', '2923', '2924', '2925', '2926', '2927', '2928', '2929', '2930', '2931', '2932', '2933', '2934', '2935', '2936', '2937', '2938', '2939', '2940', '2941', '2942', '2943', '2944', '2945', '2946', '2947', '2948', '2949', '2950', '2951', '2952', '2953', '2954', '2955', '2956', '2957', '2958', '2959', '2960', '2961', '2962', '2963', '2964', '2965', '2966', '2967', '2968', '2969', '2970', '2971', '2972', '2973', '2974', '2975', '2976', '2977', '2978', '2979', '2980', '2981', '2982', '2983', '2984', '2985', '2986', '2987', '2988', '2989', '2990', '2991', '2992', '2993', '2994', '2995', '2996', '2997', '2998', '2999']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 241, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2216, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1239, in _head
return _examples_to_batch(list(self.take(n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__
yield from islice(self.ex_iterable, self.n)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
for key, pa_table in self.generate_tables_fn(**self.kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 170, in _generate_tables
raise ValueError(
ValueError: Not able to read records in the JSON file at hf://datasets/jieyuz2/WRENCH@d1185f6cfba8d5ace2a39229799cb3f1c136bf66/classification/Bioresponse/train.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', '109', '110', '111', '112', '113', '114', '115', '116', '117', '118', '119', '120', '121', '122', '123', '124', '125', '126', '127', '128', '129', '130', '131', '132', '133', '134', '135', '136', '137', '138', '139', '140', '141', '142', '143', '144', '145', '146', '147', '148', '149', '150', '151', 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Dataset Card for WRENCH
Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development and evaluation of your own weak supervision models within the benchmark.
For more information, checkout the github repo and our publications:
- WRENCH: A Comprehensive Benchmark for Weak Supervision (NeurIPS 2021)
- A Survey on Programmatic Weak Supervision
If you find this repository helpful, feel free to cite our publication:
@inproceedings{
zhang2021wrench,
title={{WRENCH}: A Comprehensive Benchmark for Weak Supervision},
author={Jieyu Zhang and Yue Yu and Yinghao Li and Yujing Wang and Yaming Yang and Mao Yang and Alexander Ratner},
booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2021},
url={https://openreview.net/forum?id=Q9SKS5k8io}
}
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