Duplicate from sarvamai/boolq-indic

Co-authored-by: Rahul <rahular@users.noreply.huggingface.co>

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README.md

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+---
+dataset_info:
+  features:
+  - name: question
+    dtype: string
+  - name: passage
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: label
+    dtype: int64
+  - name: language
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 163090749
+    num_examples: 103697
+  - name: validation
+    num_bytes: 55710040
+    num_examples: 35970
+  download_size: 105502083
+  dataset_size: 218800789
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+license: cc-by-sa-3.0
+task_categories:
+- question-answering
+language:
+- bn
+- en
+- gu
+- hi
+- kn
+- mr
+- ml
+- or
+- pa
+- ta
+- te
+pretty_name: Indic BoolQ
+---
+
+# Indic BoolQ Dataset
+
+A multilingual version of the [BoolQ](https://huggingface.co/datasets/google/boolq) (Boolean Questions) dataset, translated from English into 10 Indian languages.
+It is a question-answering dataset for yes/no questions containing ~12k naturally occurring questions.
+
+### Languages Covered
+The dataset includes translations in the following languages:
+- Bengali (bn)
+- Gujarati (gu)
+- Hindi (hi)
+- Kannada (kn)
+- Marathi (mr)
+- Malayalam (ml)
+- Oriya (or)
+- Punjabi (pa)
+- Tamil (ta)
+- Telugu (te)
+
+### Dataset Format
+Each example contains:
+- `question`: A yes/no question in the target language
+- `passage`: A passage providing context for the question
+- `answer`: Yes/No
+- `label`: 1 for 'yes' and 0 for 'no'
+- `language`: ISO 639-1 language code
+
+## Dataset Statistics
+- Total number of examples: ~140k
+- Split sizes match the original BoolQ dataset:
+  - Training: 9,427 examples per language
+  - Validation: 3,270 examples per language
+
+## Usage
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("sarvamai/boolq-indic")
+```
+
+## License
+This dataset follows the same license as the original BoolQ dataset.
+
+## Acknowledgments
+- Original BoolQ dataset creators

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