Lots-of-LoRAs/task1712_poki_classification

该数据集名为task1712_poki_classification，属于文本生成任务类别，包含输入、输出和ID三个特征。数据集分为训练集、验证集和测试集，分别包含5158、645和645个样本。数据集的语言为英语，创建方式为众包，许可证为Apache-2.0。数据集的相关信息可以在其主页和两篇论文中找到，联系人信息也一并提供。

This dataset is crowdsourced and licensed under Apache 2.0, primarily used for text generation tasks. It includes three fields: input (string), output (string), and id (string). The dataset is divided into train, validation, and test sets, containing 5158, 645, and 645 examples respectively. The dataset is named task1712_poki_classification, part of the Natural Instructions project.

原始信息汇总

数据集概述

基本信息

• 数据集名称: task1712_poki_classification
• 数据集别名: plain_text
• 语言: 英语 (en)
• 许可证: Apache 2.0
• 任务类别: 文本生成

数据集结构

• 特征:
  • input: 字符串类型
  • output: 字符串类型
  • id: 字符串类型

数据集划分

• 训练集: 5158个样本
• 验证集: 645个样本
• 测试集: 645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}, }