The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ValueError
Message: Not able to read records in the JSON file at hf://datasets/neurotech/swahili-ner-dataset@6ec29d1f9cfc2c623d147b171247d30f3c51b550/dataset.json.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, 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 165, in _generate_tables
raise ValueError(f"Not able to read records in the JSON file at {file}.") from None
ValueError: Not able to read records in the JSON file at hf://datasets/neurotech/swahili-ner-dataset@6ec29d1f9cfc2c623d147b171247d30f3c51b550/dataset.json.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.
SWAHILI-NER-DATASET
Swahili NER dataset is a Named Entity Recognition (NER) dataset generated from https://huggingface.co/datasets/swahili using back-translation techniques.
In case you're interested to explore more about the script used to generate this dataset, please have a look into Augumented Swahili Data.
This data has been cleaned using a couple of techniques and is ready for training a Spacy NER model without any modifications, with this data we were able to train a swahili-spacy-ner.
EXPLORING DATA
Here is an example of how the dataset has been structured;
[
[
"Alisema kwamba wengi wa watoto hao wa UNCA walikuwa wanawake waliodai kwamba benki hiyo ilikuwa ikitoa mkopo kwa UNCKKKau na UNK",
{
"entities": [
[
125,
128,
"ORG"
]
]
}
],
[
"Katika mikoa ya kati mvua hutazamiwa kunyesha na dodoma kutoka maeneo ya tatu na ya nne ya novemba mwaka huu na kupimwa kwa wastani",
{
"entities": [
[
84,
87,
"ORDINAL"
]
]
}
],
.......
]
CONTRIBUTION
This dataset is open source under MIT LICENSE therefore you're warmly welcome to contribute,JUST FORK IT.
ISSUES
In case you're having any issues, please raise one so we can quickly fix it.
CREDITS
All the credits to;
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