Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models

• URL: http://arxiv.org/abs/2403.19340v2
• Date: Tue, 04 Mar 2025 03:06:30 GMT
• Title: Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models
• Authors: Hyunbyung Park, Sukyung Lee, Gyoungjin Gim, Yungi Kim, Dahyun Kim, Chanjun Park,
• Abstract summary: We propose Dataverse, a unified open-source Extract-Transform-Load (ETL) pipeline for large language models (LLMs)<n>Easy addition of custom processors with block-based interface in Dataverse allows users to readily and efficiently use Dataverse to build their own pipeline.<n>We provide a concise, two-minute video demonstration of our system, illustrating its capabilities and implementation.
• Score: 6.671352329067298
• License: http://creativecommons.org/licenses/by/4.0/
• 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 welcome community contribution. Additionally, we provide a concise, two-minute video demonstration of our system, illustrating its capabilities and implementation.

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