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Open corpus of 3T tokens for language model pretraining. Sourced from web, academic papers, code, encyclopedic, and book content.

C4 Dataset Summary A colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: "https://commoncrawl.org". This is the processed version of Google's C4 dataset We prepared five variants of the data: en, en.noclean, en.noblocklist, realnewslike, and multilingual (mC4). For reference, these are the sizes of the variants: en: 305GB en.noclean: 2.3TB en.noblocklist: 380GB realnewslike: 15GB multilingual (mC4): 9.7TB (108 subsets, one per… See the full description on the dataset page: https://huggingface.co/datasets/allenai/c4.

Dataset Card for "ai2_arc" Dataset Summary A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also including a corpus of over 14 million science sentences relevant to… See the full description on the dataset page: https://huggingface.co/datasets/allenai/ai2_arc.

Objaverse Objaverse is a Massive Dataset with 800K+ Annotated 3D Objects. More documentation is coming soon. In the meantime, please see our paper and website for additional details. License The use of the dataset as a whole is licensed under the ODC-By v1.0 license. Individual objects in Objaverse are all licensed as creative commons distributable objects, and may be under the following licenses: CC-BY 4.0 - 721K objects CC-BY-NC 4.0 - 25K objects CC-BY-NC-SA 4.0 - 52K… See the full description on the dataset page: https://huggingface.co/datasets/allenai/objaverse.

Dataset Card for OpenBookQA Dataset Summary OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic (with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In particular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge, and rich text comprehension. OpenBookQA is a new kind of… See the full description on the dataset page: https://huggingface.co/datasets/allenai/openbookqa.

Dataset Card for "winogrande" Dataset Summary WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires commonsense reasoning. Supported Tasks and Leaderboards More Information… See the full description on the dataset page: https://huggingface.co/datasets/allenai/winogrande.

Dataset Card for "sciq" Dataset Summary The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed… See the full description on the dataset page: https://huggingface.co/datasets/allenai/sciq.

MADLAD-400 Dataset and Introduction MADLAD-400 (Multilingual Audited Dataset: Low-resource And Document-level) is a document-level multilingual dataset based on Common Crawl, covering 419 languages in total. This uses all snapshots of CommonCrawl available as of August 1, 2022. The primary advantage of this dataset over similar datasets is that it is more multilingual (419 languages), it is audited and more highly filtered, and it is document-level. The main disadvantage… See the full description on the dataset page: https://huggingface.co/datasets/allenai/MADLAD-400.

Dataset Card for Situations With Adversarial Generations Dataset Summary Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine"). SWAG (Situations With Adversarial Generations) is a large-scale dataset for this task of grounded commonsense inference, unifying natural language inference and physically grounded reasoning. The dataset consists of 113k… See the full description on the dataset page: https://huggingface.co/datasets/allenai/swag.

Dataset Card for "quartz" Dataset Summary QuaRTz is a crowdsourced dataset of 3864 multiple-choice questions about open domain qualitative relationships. Each question is paired with one of 405 different background sentences (sometimes short paragraphs). The QuaRTz dataset V1 contains 3864 questions about open domain qualitative relationships. Each question is paired with one of 405 different background sentences (sometimes short paragraphs). The dataset is split into… See the full description on the dataset page: https://huggingface.co/datasets/allenai/quartz.

Dataset Card for "qasc" Dataset Summary QASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice questions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed Dataset Structure Data Instances default Size of… See the full description on the dataset page: https://huggingface.co/datasets/allenai/qasc.

⚠️ WARNING: This dataset is intended ONLY for reproducing Olmo 3 7B ⚠️ For all other training use cases, including training from scratch, please utilize our primary dolma 3 data mix: https://huggingface.co/datasets/allenai/dolma3_mix-6T. Note: Some olmOCR science PDFs in the current dataset have been redacted following the training of Olmo 3 7B. These texts are indicated with [REMOVED] in the text field. This will affect reproducibility of Olmo 3 7B. For this reason, please use our… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_mix-6T-1025-7B.

MolmoAct - Midtraining Mixture Data Mixture used for MolmoAct Midtraining. Contains MolmoAct Dataset formulated as Action Reasoning Data. MolmoAct is a fully open-source action reasoning model for robotic manipulation developed by the Allen Institute for AI. MolmoAct is trained on a subset of OXE and MolmoAct Dataset, a dataset with 10k high-quality trajectories of a single-arm Franka robot performing 93 unique manipulation tasks in both home and tabletop environments. It has… See the full description on the dataset page: https://huggingface.co/datasets/allenai/MolmoAct-Midtraining-Mixture.