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README.md
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- split: train
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path: data/train-*
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---
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- split: train
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path: data/train-*
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---
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# mkqa filtered version
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For a better dataset description, please visit the official site of the source dataset: [LINK](https://huggingface.co/datasets/mkqa) <br>
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<br>
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**This dataset was prepared by converting mkqa dataset**.
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**I additionaly share the code which I used to convert the original dataset to make everything more clear**
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```
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mkqa = load_dataset("mkqa", split="train").to_pandas()
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needed_langs = ["en", "ar", "de", "es", "vi", "zh_cn"]
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rows = []
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for i, row in tqdm(mkqa.iterrows(), total=mkqa.shape[0]):
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for lang in needed_langs:
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rows.append([lang, row["example_id"], row["queries"][lang], row["answers"][lang][0]["text"]])
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filtered_dataset = pd.DataFrame(rows, columns=["lang", "example_id", "query", "answer"])
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filtered_dataset.dropna(inplace=True)
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filtered_dataset.reset_index(drop=True, inplace=True)
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```
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**How to download**
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```
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from datasets import load_dataset
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data = load_dataset("dkoterwa/oasst1_filtered_retrieval")
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```
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