Lots-of-LoRAs/task393_plausible_result_generation

该数据集名为task393_plausible_result_generation，属于自然指令（Natural Instructions）项目的一部分。数据集的任务是生成合理的结果，适用于文本生成任务。数据集包含80个训练样本、10个验证样本和10个测试样本。每个样本包含输入、输出和ID三个特征。

The dataset is named task393_plausible_result_generation and is part of the Natural Instructions project. The task of the dataset is to generate plausible results, suitable for text generation tasks. The dataset contains 80 training examples, 10 validation examples, and 10 test examples. Each example includes three features: input, output, and ID.

原始信息汇总

数据集概述

基本信息

• 数据集名称: task393_plausible_result_generation
• 数据集别名: Natural Instructions
• 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

• 配置名称: plain_text
• 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: 80个样本
• 验证集: 10个样本
• 测试集: 10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}, }