datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
china-effective-laws-regulations
全国现行法律法规合集
现行有效的中华人民共和国法律、行政法规、监察法规、地方性法规、司法解释结构化文本。一部法规一行，一条法条一行，供查阅、检索、RAG 和法律 NLP 使用。
数据来自全国人大常委会办公厅 国家法律法规数据库，下载口径为官网的 「有效及尚未生效」。正文由 Word 原文用脚本抽取，未经大模型改写。
这不是官方汇编，不能替代公报或标准文本，也不能作为法律意见。 电子文本与标准文本不一致时，以法律规定的标准文本为准。
快照日期：2026-08-26
效力说明
本数据集 以现行有效法律法规为主体：
效力 status
法规份数
说明
有效
17,649
现行有效，默认应使用这一部分
尚未生效
7
已公布、施行日晚于快照日
失效
45
文件名含「失效」，多为已到期的全国人大常委会试点授权决定
使用时请筛选 status == "有效"，即可得到现行有效文本。同一部法若有修正前后多个版本，均予保留，用 filename_date 区分，采用最新日期即可。… See the full description on the dataset page: https://huggingface.co/datasets/senry5433/china-effective-laws-regulations.task828_copa_commonsense_cause_effect
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task828_copa_commonsense_cause_effect
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task828_copa_commonsense_cause_effect.ArXiv-10
ArXiv-10
"ArXiv-10" dataset consists of titles and abstracts extracted from 100k scientific papers on ArXiv, covering ten distinct research categories.
These categories includes subfields of computer science, physics, and mathematics.
To ensure consistency and manageability, the dataset consists of precisely 10k samples per category.
This dataset provides a practical resource for researchers and practitioners interested in LLM.
What is different about this dataset is the high… See the full description on the dataset page: https://huggingface.co/datasets/effectiveML/ArXiv-10.Agent-eval-Effector-Hunt
Agent Eval: Effector Hunt
While AI scientist agents like Claude Science and Google's AI co-scientist highlight the potential of autonomous research, compact and reproducible datasets for evaluating these agents on real scientific workflows remain scarce.
Agent Eval: Effector Hunt is a genomics benchmark package designed around a real scientific discovery workflow from the Science paper Chen et al. 2017. It asks an AI agent, a computational biologist, or a hybrid human-agent… See the full description on the dataset page: https://huggingface.co/datasets/chjp0632/Agent-eval-Effector-Hunt.task1727_wiqa_what_is_the_effect
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1727_wiqa_what_is_the_effect
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1727_wiqa_what_is_the_effect.go-effective-docs-qa
Effective Go Instruction Dataset
Overview
This dataset was created from the official Effective Go documentation. The content was extracted from:
https://go.dev/doc/effective_go
and transformed into instruction-following samples consisting of:
instruction
input
output
Dataset Structure
Split
Examples
Train
2,643
Validation
293
Features
instruction (string)
input (string)
output (string)
How this… See the full description on the dataset page: https://huggingface.co/datasets/farid678/go-effective-docs-qa.