Prompto: An open source library for asynchronous querying of LLM endpoints

-д хадгалсан:

Номзүйн дэлгэрэнгүй
-д хэвлэсэн:	arXiv.org (Dec 16, 2024), p. n/a
Үндсэн зохиолч:	Chan, Ryan Sze-Yin
Бусад зохиолчид:	Nanni, Federico, Williams, Angus R, Brown, Edwin, Burke-Moore, Liam, Chapman, Ed, Onslow, Kate, Sippy, Tvesha, Bright, Jonathan, Gabasova, Evelina
Хэвлэсэн:	Cornell University Library, arXiv.org
Нөхцлүүд:	Comparative studies Availability Python Large language models
Онлайн хандалт:	Citation/Abstract Full text outside of ProQuest
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!

Тодорхойлолт
Хураангуй:	Recent surge in Large Language Model (LLM) availability has opened exciting avenues for research. However, efficiently interacting with these models presents a significant hurdle since LLMs often reside on proprietary or self-hosted API endpoints, each requiring custom code for interaction. Conducting comparative studies between different models can therefore be time-consuming and necessitate significant engineering effort, hindering research efficiency and reproducibility. To address these challenges, we present prompto, an open source Python library which facilitates asynchronous querying of LLM endpoints enabling researchers to interact with multiple LLMs concurrently, while maximising efficiency and utilising individual rate limits. Our library empowers researchers and developers to interact with LLMs more effectively and allowing faster experimentation, data generation and evaluation. prompto is released with an introductory video (https://youtu.be/lWN9hXBOLyQ) under MIT License and is available via GitHub (https://github.com/alan-turing-institute/prompto).
ISSN:	2331-8422
Эх сурвалж:	Engineering Database