HuggingFaceFW/fineweb
FineWeb is a dataset of over 15 trillion tokens of cleaned and deduplicated English web data from CommonCrawl. It is optimized for LLM performance and processed using the datatrove library. The dataset aims to provide high-quality data for training large language models and outperforms other commonly used web datasets.We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Detaljert introduksjon
FineWeb is a large-scale dataset designed to provide high-quality web data for training large language models. It includes over 15 trillion tokens of cleaned and deduplicated English web data from CommonCrawl. The dataset is processed using the datatrove library and is optimized for LLM performance. It outperforms other commonly used web datasets in benchmark tasks.
MerDatasett
HuggingFaceFW/fineweb-2
FineWeb-2 is a dataset of over 15 trillion tokens of cleaned and deduplicated English web data from CommonCrawl. This is the second iteration of the popular 🍷 FineWeb dataset, bringing high quality pretraining data to over 1000 🗣️ languages.The 🥂 FineWeb2 dataset is fully reproducible, available under the permissive ODC-By 1.0 license and extensively validated through hundreds of ablation experiments.In particular, on the set of 9 diverse languages we used to guide our processing decisions, 🥂 FineWeb2 outperforms other popular pretraining datasets covering multiple languages (such as CC-100, mC4, CulturaX or HPLT, while being substantially larger) and, in some cases, even performs better than some datasets specifically curated for a single one of these languages, in our diverse set of carefully selected evaluation tasks: FineTasks.
Hugging Face Dataset - bfuzzy1/gunny_x
Every veteran knows and has had a 'Gunny': Semper Fidelis. This dataset is designed for conversational AI systems to assist veterans from various military branches, including U.S. and U.K. armed forces.
Psychology Wiki Dataset
Psychology Wiki Datasetpsychology_wiki数据集的构建基于心理学领域的英文维基百科内容，通过系统化的数据采集与整理，确保了信息的广泛覆盖与深度挖掘。数据集中的每一篇文章均经过严格的筛选与标注，涵盖了标题、正文、相关性、受欢迎程度及排名等多个维度，为心理学研究提供了丰富的文本资源。