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Datasets:
rag-datasets
/
rag-mini-wikipedia

Tasks:
Question Answering
Sentence Similarity
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1K - 10K
Tags:
rag
wikipedia
open-domain
information-retrieval
dpr
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
1
tillwenke commited on
Commit
87c787b
•
1 Parent(s): 146c5e7

init with dataset as parquet

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Files changed (50) hide show
  1. .gitattributes +2 -0
  2. .gitignore +1 -0
  3. dataset/eval.parquet +3 -0
  4. dataset/passages.parquet/part.0.parquet +3 -0
  5. dataset/passages.parquet/part.1.parquet +3 -0
  6. dataset/passages.parquet/part.2.parquet +3 -0
  7. dataset/passages.parquet/part.3.parquet +3 -0
  8. generate.py +32 -0
  9. raw_data/S08_question_answer_pairs.txt +3 -0
  10. raw_data/S09_question_answer_pairs.txt +3 -0
  11. raw_data/S10_question_answer_pairs.txt +3 -0
  12. raw_data/text_data/S08_set1_a1.txt.clean +3 -0
  13. raw_data/text_data/S08_set1_a10.txt.clean +3 -0
  14. raw_data/text_data/S08_set1_a2.txt.clean +3 -0
  15. raw_data/text_data/S08_set1_a3.txt.clean +3 -0
  16. raw_data/text_data/S08_set1_a4.txt.clean +3 -0
  17. raw_data/text_data/S08_set1_a5.txt.clean +3 -0
  18. raw_data/text_data/S08_set1_a6.txt.clean +3 -0
  19. raw_data/text_data/S08_set1_a7.txt.clean +3 -0
  20. raw_data/text_data/S08_set1_a8.txt.clean +3 -0
  21. raw_data/text_data/S08_set1_a9.txt.clean +3 -0
  22. raw_data/text_data/S08_set1_topics.txt +3 -0
  23. raw_data/text_data/S08_set2_a1.txt.clean +3 -0
  24. raw_data/text_data/S08_set2_a10.txt.clean +3 -0
  25. raw_data/text_data/S08_set2_a2.txt.clean +3 -0
  26. raw_data/text_data/S08_set2_a3.txt.clean +3 -0
  27. raw_data/text_data/S08_set2_a4.txt.clean +3 -0
  28. raw_data/text_data/S08_set2_a5.txt.clean +3 -0
  29. raw_data/text_data/S08_set2_a6.txt.clean +3 -0
  30. raw_data/text_data/S08_set2_a7.txt.clean +3 -0
  31. raw_data/text_data/S08_set2_a8.txt.clean +3 -0
  32. raw_data/text_data/S08_set2_a9.txt.clean +3 -0
  33. raw_data/text_data/S08_set2_topics.txt +3 -0
  34. raw_data/text_data/S08_set3_a1.txt.clean +3 -0
  35. raw_data/text_data/S08_set3_a10.txt.clean +3 -0
  36. raw_data/text_data/S08_set3_a2.txt.clean +3 -0
  37. raw_data/text_data/S08_set3_a3.txt.clean +3 -0
  38. raw_data/text_data/S08_set3_a4.txt.clean +3 -0
  39. raw_data/text_data/S08_set3_a5.txt.clean +3 -0
  40. raw_data/text_data/S08_set3_a6.txt.clean +3 -0
  41. raw_data/text_data/S08_set3_a7.txt.clean +3 -0
  42. raw_data/text_data/S08_set3_a8.txt.clean +3 -0
  43. raw_data/text_data/S08_set3_a9.txt.clean +3 -0
  44. raw_data/text_data/S08_set3_topics.txt +3 -0
  45. raw_data/text_data/S08_set4_a1.txt.clean +3 -0
  46. raw_data/text_data/S08_set4_a10.txt.clean +3 -0
  47. raw_data/text_data/S08_set4_a2.txt.clean +3 -0
  48. raw_data/text_data/S08_set4_a3.txt.clean +3 -0
  49. raw_data/text_data/S08_set4_a4.txt.clean +3 -0
  50. raw_data/text_data/S08_set4_a5.txt.clean +3 -0
.gitattributes CHANGED
@@ -53,3 +53,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
53
  *.jpg filter=lfs diff=lfs merge=lfs -text
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  *.jpeg filter=lfs diff=lfs merge=lfs -text
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  *.webp filter=lfs diff=lfs merge=lfs -text
 
 
 
53
  *.jpg filter=lfs diff=lfs merge=lfs -text
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  *.jpeg filter=lfs diff=lfs merge=lfs -text
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  *.webp filter=lfs diff=lfs merge=lfs -text
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+ # custom
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+ raw_data/** filter=lfs diff=lfs merge=lfs -text
.gitignore ADDED
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dataset/eval.parquet ADDED
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generate.py ADDED
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+ # from https://www.kaggle.com/datasets/rtatman/questionanswer-dataset/
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+ import pandas as pd
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+ import glob
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+ import dask.dataframe as dd
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+
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+
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+ path_to_file = "./raw_data/S08_question_answer_pairs.txt"
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+
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+ df = pd.read_csv(path_to_file, sep="\t")
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+ df.rename(columns={"Question": "question", "Answer": "answer"}, inplace=True)
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+ df = df[["question", "answer"]]
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+ df = df.dropna()
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+ df = df.drop_duplicates(subset="question")
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+ path_to_file = "./dataseeval.parquet"
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+
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+ df.to_parquet(path_to_file)
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+
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+ path_to_file = "./raw_data/text_data/S08*clean"
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+
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+ s08 = glob.glob(path_to_file)
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+ passages = pd.DataFrame(columns=["passage"])
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+ for file in s08:
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+ df = pd.read_csv(file, sep="\t", encoding="latin-1", index_col=False)
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+ df.rename(columns={df.columns[0]: "passage"}, inplace=True)
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+ passages = pd.concat([passages, df], axis=0, ignore_index=True)
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+ passages = passages.dropna()
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+ passages.index = passages.index.astype(str)
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+
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+
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+ path_to_file = "./dataset/passages.parquet"
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+
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+ dd.from_pandas(passages, npartitions=4).to_parquet(path_to_file)
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