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Lots-of-LoRAs/task1294_wiki_qa_answer_verification

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Hugging Face2024-07-16 更新2024-07-06 收录
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资源简介:
该数据集名为task1294_wiki_qa_answer_verification,属于文本生成任务类别,主要用于维基问答的答案验证。数据集包含训练集、验证集和测试集,分别有1756、219和220个样本。每个样本包含输入、输出和ID三个特征。

The dataset is named task1294_wiki_qa_answer_verification and belongs to the text generation task category, primarily used for Wikipedia QA answer verification. The dataset includes training, validation, and test sets with 1756, 219, and 220 samples respectively. Each sample contains three features: input, output, and ID.
提供机构:
Lots-of-LoRAs
原始信息汇总

数据集概述

基本信息

  • 数据集名称: task1294_wiki_qa_answer_verification
  • 任务类别: 文本生成
  • 语言: 英语
  • 许可证: Apache 2.0

数据集详情

  • 配置名称: plain_text
  • 特征:
    • input: 字符串类型
    • output: 字符串类型
    • id: 字符串类型
  • 数据分割:
    • 训练集: 1756个样本
    • 验证集: 219个样本
    • 测试集: 220个样本

引用信息

  • 主要引用: bibtex @misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions, title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}, author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi}, year={2022}, eprint={2204.07705}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2204.07705}, }

  • 额外引用: bibtex @misc{brüelgabrielsson2024compressserveservingthousands, title={Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead}, author={Rickard Brüel-Gabrielsson and Jiacheng Zhu and Onkar Bhardwaj and Leshem Choshen and Kristjan Greenewald and Mikhail Yurochkin and Justin Solomon}, year={2024}, eprint={2407.00066}, archivePrefix={arXiv}, primaryClass={cs.DC}, url={https://arxiv.org/abs/2407.00066}, }

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