datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
qg_squad_modifiedqg_squad_modified_devLearningQ-qg
Dataset Card for LearningQ-qg
Dataset Summary
LearningQ, a challenging educational question generation dataset containing over 230K document-question pairs by [Guanliang Chen, Jie Yang, Claudia Hauff and Geert-Jan Houben]. It includes 7K instructor-designed questions assessing knowledge concepts being taught and 223K learner-generated questions seeking in-depth understanding of the taught concepts. This new version collected and corrected from over than 50000 error and… See the full description on the dataset page: https://huggingface.co/datasets/sidovic/LearningQ-qg.twitter_author_profiling_by_gender_nlpThis dataset was created for a student's Bc work.
The main purpose for which the dataset was created is to use it in author profiling by gender.
Single-Tweet-Per-Author Twitter Dataset
Overview
This dataset consists of Twitter (X) posts with a strict constraint: each author appears exactly once.There is a one-to-one correspondence between tweets and authors.
This design removes author-level accumulation effects and prevents models from exploiting repeated stylistic or… See the full description on the dataset page: https://huggingface.co/datasets/qg2020252627/twitter_author_profiling_by_gender_nlp.QGCNQ
Dataset Card for Dataset Name
QGCNQ – Quantum Mechanics, Genetics, Cosmology, Neuroscience, Cognitive Science Questions
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More Information Needed]
Paper… See the full description on the dataset page: https://huggingface.co/datasets/T404C/QGCNQ.IT_QA-QGbalanced_qgqgelm-ranksQG_datasetskripsi-qg-evaluation-resultsQG_pythonQG_PythonWithHigheRrougeoop-de-qg-v2qgelm_first_lastQGdata
QG工作室人工智能组培训数据集
机器学习培训阶段专用数据集
数据集说明
数据集包含训练集train、测试集test
最后一列为标签，其余列为特征
完成分类任务后，需对模型进行合理的全面评估，指标至少包括Accuracy、Precision、Recall、F1-score 以及 ROC-AUC 曲线，评估指标不设上限
Designed by yrui | QG Studio AI Group | 2026.03
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