March 29, 2024, 4:48 a.m. | Hyunbyung Park, Sukyung Lee, Gyoungjin Gim, Yungi Kim, Dahyun Kim, Chanjun Park

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.19340v1 Announce Type: new
Abstract: To address the challenges associated with data processing at scale, we propose Dataverse, a unified open-source Extract-Transform-Load (ETL) pipeline for large language models (LLMs) with a user-friendly design at its core. Easy addition of custom processors with block-based interface in Dataverse allows users to readily and efficiently use Dataverse to build their own ETL pipeline. We hope that Dataverse will serve as a vital tool for LLM development and open source the entire library to …

abstract arxiv block challenges core cs.ai cs.cl data data processing design easy etl extract language language models large language large language models llms pipeline processing processors scale type

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Analyst (Digital Business Analyst)

@ Activate Interactive Pte Ltd | Singapore, Central Singapore, Singapore