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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:    ArrowInvalid
Message:      Schema at index 1 was different: 
title: string
author: string
sequenced: bool
format: int64
url: string
isUpdatable: bool
indexUrl: string
downloadUrl: string
sourceLanguage: string
targetLanguage: string
description: string
attribution: string
revision: string
vs
0: string
1: string
2: int64
3: string
4: int64
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, 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 3357, 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 2111, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2315, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 520, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              title: string
              author: string
              sequenced: bool
              format: int64
              url: string
              isUpdatable: bool
              indexUrl: string
              downloadUrl: string
              sourceLanguage: string
              targetLanguage: string
              description: string
              attribution: string
              revision: string
              vs
              0: string
              1: string
              2: int64
              3: string
              4: int64

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YAML Metadata Warning: The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Jitendex for Language Models (JT4LLM)

Dataset Summary

JT4LLM is a reprocessed version of Jitendex Japanese-to-English dictionary for language models. It contains over 250K lines of terms and definitions for Japanese learners.

  • Curated by: KaraKaraWitch
  • Funded by: Recursal.ai
  • Shared by: KaraKaraWitch
  • Language(s) (NLP): English & Japanese. Other languages are available at tiny sizes.
  • License: Scripts folder are Apache 2.0. Refer to Licensing Information for data license (CC-BY-SA).

Dataset Sources

NOTE

/!\ This dataset card is incomplete! I'm waiting on some legalize before I move it to recursal/featherless org. :) /!\

Licensing Information

The base dataset (Jitendex) is licensed under CC-BY-SA. Additionally Jitendex include the following other sources such as:

* Kanji Alive audio data & furigana positional information are not included in this specific dataset.

Funding

If you like this dataset, consider supporting Jitendex directly via Ko-Fi or giving the project a star on GitHub.

Disclaimers

  • KaraKaraWitch & recursal/featherless.ai are not affiliated with the creators of Jitendex.
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