five

irds/lotte_writing_test

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Hugging Face2023-01-05 更新2024-03-04 收录
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资源简介:
--- pretty_name: '`lotte/writing/test`' viewer: false source_datasets: [] task_categories: - text-retrieval --- # Dataset Card for `lotte/writing/test` The `lotte/writing/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/test). # Data This dataset provides: - `docs` (documents, i.e., the corpus); count=199,994 This dataset is used by: [`lotte_writing_test_forum`](https://huggingface.co/datasets/irds/lotte_writing_test_forum), [`lotte_writing_test_search`](https://huggingface.co/datasets/irds/lotte_writing_test_search) ## Usage ```python from datasets import load_dataset docs = load_dataset('irds/lotte_writing_test', 'docs') for record in docs: record # {'doc_id': ..., 'text': ...} ``` Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the data in 🤗 Dataset format. ## Citation Information ``` @article{Santhanam2021ColBERTv2, title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction", author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia", journal= "arXiv preprint arXiv:2112.01488", year = "2021", url = "https://arxiv.org/abs/2112.01488" } ```
提供机构:
irds
原始信息汇总

数据集概述

数据集名称

  • 名称:lotte/writing/test

数据来源

数据内容

  • 类型:文本检索
  • 数据集包含:
    • docs(文档,即语料库);数量=199,994

数据使用

  • 使用示例: python from datasets import load_dataset

    docs = load_dataset(irds/lotte_writing_test, docs) for record in docs: record # {doc_id: ..., text: ...}

引用信息

  • 引用文献:

    @article{Santhanam2021ColBERTv2, title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction", author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia", journal= "arXiv preprint arXiv:2112.01488", year = "2021", url = "https://arxiv.org/abs/2112.01488" }

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