Lots-of-LoRAs/task1583_bless_meronym_classification

该数据集名为task1583_bless_meronym_classification，主要用于文本生成任务，具体任务涉及部分与整体关系的分类。数据集包含训练集、验证集和测试集，分别有1184、148和149个样本。数据集的创建者是通过众包方式完成的，语言为英语，许可证为Apache-2.0。

The dataset is named task1583_bless_meronym_classification and is primarily used for text generation tasks, specifically focusing on the classification of part-whole relationships. The dataset includes training, validation, and test sets with 1184, 148, and 149 examples respectively. The dataset was created through crowdsourcing, is in English, and 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: task1583_bless_meronym_classification
• 语言: 英语 (en)
• 许可证: Apache 2.0
• 任务类别: 文本生成

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: 1184个样本
  • 验证集: 148个样本
  • 测试集: 149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}, }

• 附加引用: 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}, }