Datasets:

QuarkML
/

English-Hindi-Cleaned-Subset-IIT-Bombay

Tasks:

Translation

Languages:

English

Hindi

Size:

100K<n<1M

License:

Dataset card Files Files and versions

xet

Community

Dataset Viewer

Split (1)

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:    ArrowInvalid
Message:      JSON parse error: Column() changed from object to string in row 0
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
                  df = pandas_read_json(f)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
                  obj = self._get_object_parser(self.data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
                  self._parse()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1402, in _parse
                  self.obj = DataFrame(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/frame.py", line 778, in __init__
                  mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
                  return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
                  index = _extract_index(arrays)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 680, in _extract_index
                  raise ValueError(
              ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.
              
              During handling of the above exception, another exception occurred:
              
              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 476, in _iter_arrow
                  for key, pa_table in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 323, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 163, in _generate_tables
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
                  pa_table = paj.read_json(
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                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: JSON parse error: Column() changed from object to string in row 0

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IIT-Bombay EN–HI Subset

A filtered subset of the IIT-Bombay English–Hindi Parallel Corpus, created by preprocessing and selecting the highest-quality sentence pairs for research on English→Hindi translation.

Dataset Summary

Language pair: English ↔ Hindi
Total sentences: 227122

This subset was produced by:

Cleaning: removing non-UTF8, overly short/long, and misaligned pairs
Filtering: selecting sentences with high-quality alignment scores
Normalization: lowercasing English, standardizing Hindi Unicode forms

Supported Tasks and Leaderboards

Task: Machine Translation (English→Hindi)
No benchmark leaderboard yet—intended primarily as a study dataset.

Languages

Language	Code
English	`en`
Hindi	`hi`

Dataset Structure

This subset is provided as two parallel text files:

english_subset.txt: one English sentence per line
hindi_subset.txt: corresponding Hindi sentence per line (Devanagari)

Line i in both files form a parallel pair. Example (line 1 in both files):


english\_subset.txt: How are you doing today?

hindi\_subset.txt:  आप आज कैसे हैं?

Usage

from datasets import load_dataset

# load from local files
data_files = {
    'train': ['english_subset.txt', 'hindi_subset.txt']
}
dataset = load_dataset(
    'text',
    data_files=data_files,
    split='train'
)
# then rename columns
paired = dataset.map(lambda x, idx: {'en': x['text'][idx], 'hi': dataset['train']['text'][idx]}, with_indices=True)
print(paired[0])

Alternatively, if hosted on HF:

from datasets import load_dataset

dataset = load_dataset("QuarkML/English-Hindi-Cleaned-Subset-IIT-Bombay")
print(dataset['train'][0])

License

This subset is released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Use, share, and adapt for non-commercial purposes only, give appropriate credit, and distribute derivatives under the same license.

Full details: https://creativecommons.org/licenses/by-nc-sa/4.0/

Acknowledgements

Original corpus by A. Kunchukuttan et al. (LREC 2018).
Maintained and subset by Sidharth GN / Quark Machine Learning.

Contact

If you encounter issues or have questions, please open an issue on this repo or contact [email protected].

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