Lots-of-LoRAs/task201_mnli_neutral_classification

该数据集名为task201_mnli_neutral_classification，属于文本生成任务类别。数据集包含5200个训练样本、650个验证样本和650个测试样本。每个样本包含输入、输出和ID三个特征。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。更多详细信息可以参考数据集的主页和相关论文。

The dataset is named task201_mnli_neutral_classification and belongs to the text-generation task category. It contains 5200 training examples, 650 validation examples, and 650 test examples. Each example includes three features: input, output, and ID. The dataset is in English, and both the annotations and language creators are crowdsourced. The dataset is licensed under Apache-2.0. More details can be found on the datasets homepage and related papers.

原始信息汇总

数据集概述

基本信息

• 数据集名称: task201_mnli_neutral_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 (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: 5200 个样本
• 验证集: 650 个样本
• 测试集: 650 个样本

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}, }