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.
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.
The ToM QA Dataset is designed to evaluate question-answering models' ability to reason about beliefs. It includes 3 task types and 4 question types, creating 12 total scenarios. The dataset is inspired by theory-of-mind experiments in developmental psychology and is used to test models' understanding of beliefs and inconsistent states of the world.
The ISSP is a cross-national collaboration program conducting annual surveys on diverse topics relevant to social sciences. It includes members from various cultures around the globe and provides free access to collected data and documentation.
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.