Tokenized Data for FORGE Foundation Models
- Yin, Junqi | Oak Ridge National Laboratory
- Dash, Sajal | Oak Ridge National Laboratory
- Wang, Feiyi | Oak Ridge National Laboratory
- Shankar, Mallikarjun (Arjun) | Oak Ridge National Laboratory
Overview
Description
This dataset comprises a vast corpus of 257 billion tokens, accompanied by the corresponding vocabulary file employed in the pre-training of FORGE foundation models. The primary data source for this corpus is scientific documents derived from diverse origins, and they have been tokenized using the Hugging Face BPE tokenizer. Further details about this research can be found in the publication titled FORGE: Pre-Training Open Foundation Models for Science authored by Junqi Yin, Sajal Dash, Feiyi Wang, and Mallikarjun (Arjun) Shankar, presented at SC'23. The data tokenization pipeline and resulting artifacts use CORE data [Ref: Knoth, P., and Zdrahal, Z. (2012). CORE: three access levels to underpin open access. D-Lib Magazine, 18(11/12)]. For use of these data sets for any purpose, please follow the guidelines provided in https://core.ac.uk/terms .
Funding Resources
DOE Contract Number
DE-AC05-00OR22725Originating Research Organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Sponsoring Organization
Office of Science (SC)Project Identifier
OLCF-6 BenchmarkDetails
DOI
10.13139/OLCF/2004951Release Date
October 18, 2023Dataset
Dataset Type
SM Specialized MixSoftware
FORGEAcknowledgements
Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.