language:hi license:apache-2.0 size_categories:10K<n<100K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: context
    dtype: string
  - name: Question
    dtype: string
  - name: RAW Ground Truth
    sequence: string
  - name: Thinking
    dtype: string
  - name: Final Answer
    dtype: string
  splits:
  - name: train
    num_bytes: 127563197
    num_examples: 19083
  download_size: 50023412
  dataset_size: 127563197
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
language:
- hi
license: apache-2.0
---


```python
>>> from datasets import load_dataset

>>> ds = load_dataset("jaeyong2/hi-rag-cot", split="train")
>>> ds
Dataset({
    features: ['context', 'Question', 'RAW Ground Truth', 'Thinking', 'Final Answer'],
    num_rows: 19083
})
```


### Development Process

1. source dataset from [Cohere/wikipedia-22-12-hi-embeddings](https://huggingface.co/datasets/Cohere/wikipedia-22-12-hi-embeddings)
2. We used [Qwen/Qwen2-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) model to generate answer with COT.




## License
- Qwen/Qwen2.5-72B-Instruct : https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
- Cohere/wikipedia-22-12-hi-embeddings : https://choosealicense.com/licenses/apache-2.0/


## Acknowledgement
This research is supported by **TPU Research Cloud program**.