March 27, 2024, 4:48 a.m. | Jinyi Li, Yihuai Lan, Lei Wang, Hao Wang

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.17411v1 Announce Type: new
Abstract: Prompt compression is an innovative method for efficiently condensing input prompts while preserving essential information. To facilitate quick-start services, user-friendly interfaces, and compatibility with common datasets and metrics, we present the Prompt Compression Toolkit (PCToolkit). This toolkit is a unified plug-and-play solution for compressing prompts in Large Language Models (LLMs), featuring cutting-edge prompt compressors, diverse datasets, and metrics for comprehensive performance evaluation. PCToolkit boasts a modular design, allowing for easy integration of new datasets and …

abstract arxiv compression cs.cl datasets information interfaces language language models large language large language models metrics prompt prompts services solution the prompt toolkit type

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

AIML - Sr Machine Learning Engineer, Data and ML Innovation

@ Apple | Seattle, WA, United States

Senior Data Engineer

@ Palta | Palta Cyprus, Palta Warsaw, Palta remote