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lilac-pile-of-law-r-legaladvice

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train

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/lilacai/lilac-pile-of-law-r-legaladvice@c8689c8d90f1f20a1f19037d71339b6712ec6c53/lilac/pile-of-law-r-legaladvice/text/lilac/legal-termination/gte-small/v33/signal_manifest.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['files', 'parquet_id', 'data_schema', 'signal', 'enriched_path']. 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/lilacai/lilac-pile-of-law-r-legaladvice@c8689c8d90f1f20a1f19037d71339b6712ec6c53/lilac/pile-of-law-r-legaladvice/text/lilac/legal-termination/gte-small/v33/signal_manifest.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['files', 'parquet_id', 'data_schema', 'signal', 'enriched_path']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.

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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

This dataset is generated by Lilac for a HuggingFace Space: huggingface.co/spaces/lilacai/lilac.

Original dataset: https://huggingface.co/datasets/pile-of-law/pile-of-law

Lilac dataset config:

- {embedding: gte-small, path: text}
name: pile-of-law-r-legaladvice
namespace: lilac
settings:
  preferred_embedding: gte-small
  ui:
    media_paths: [text]
signals:
- path: text
  signal: {signal_name: near_dup}
- path: text
  signal: {signal_name: text_statistics}
- path: text
  signal: {signal_name: pii}
- path: text
  signal: {signal_name: lang_detection}
- path: text
  signal: {signal_name: spacy_ner}
- path: text
  signal: {concept_name: positive-sentiment, embedding: gte-small, namespace: lilac,
    signal_name: concept_score}
- path: text
  signal: {concept_name: toxicity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
  signal: {concept_name: non-english, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
  signal: {concept_name: negative-sentiment, embedding: gte-small, namespace: lilac,
    signal_name: concept_score}
- path: text
  signal: {concept_name: profanity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
  signal: {concept_name: source-code, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
  signal: {concept_name: legal-termination, embedding: gte-small, namespace: lilac,
    signal_name: concept_score}
- path: text
  signal: {concept_name: question, embedding: gte-small, namespace: lilac, signal_name: concept_score}
source: {config_name: r_legaladvice, dataset_name: pile-of-law/pile-of-law, source_name: huggingface}
tags: [legal]

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