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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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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
- Source Data: Jitendex.org by (Stephen Kraus)
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:
- JMdict (EDICT, etc.) by the Electronic Dictionaries Research Group (EDRG). CC-BY-SA License Infomation
- Example sentences (Japanese <-> English) by Tatoeba. CC-BY 2.0 FR License Infomation
- Example pronunciation audio by Kanji Alive. Creative Commons Attribution 4.0 International License*
- Positional information for the furigana displayed in headwords by JmdictFurigana. CC-BY-SA License Infomation (License is the same as JMDict.)
* 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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