Lots-of-LoRAs/task1328_qa_zre_relation_generation_from_question

该数据集名为task1328_qa_zre_relation_generation_from_question，属于自然指令（Natural Instructions）项目的一部分，主要用于文本生成任务。数据集包含训练、验证和测试三个分割，分别有4672、584和584个样本。每个样本包含输入、输出和ID三个特征，输入和输出均为字符串类型。数据集的语言为英语，创建者和语言创建者均为众包。数据集的许可证为Apache-2.0。

The dataset, named task1328_qa_zre_relation_generation_from_question, is part of the Natural Instructions project and is primarily used for text generation tasks. It includes training, validation, and test splits with 4672, 584, and 584 examples respectively. Each example contains three features: input, output, and ID, with both input and output being of string type. The dataset is in English, with both annotations and language creators being crowdsourced. The dataset is licensed under Apache-2.0.

原始信息汇总

数据集概述

基本信息

• 数据集名称: task1328_qa_zre_relation_generation_from_question
• 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 (text-generation)

数据集结构

特征

• input: 字符串类型 (string)
• output: 字符串类型 (string)
• id: 字符串类型 (string)

数据分割

• 训练集 (train): 4672 条数据
• 验证集 (valid): 584 条数据
• 测试集 (test): 584 条数据

引用信息

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}, }

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}, }

联系信息

• 联系人: Rickard Brüel Gabrielsson
• 邮箱: [e-mail]