The PLLuM Instruction Corpus
cs.CL
/ Authors
Piotr Pęzik, Filip Żarnecki, Konrad Kaczyński, Anna Cichosz, Zuzanna Deckert, Monika Garnys, Izabela Grabarczyk, Wojciech Janowski, Sylwia Karasińska, Aleksandra Kujawiak
and 43 more authors
Piotr Misztela, Maria Szymańska, Karolina Walkusz, Igor Siek, Maciej Chrabąszcz, Anna Kołos, Agnieszka Karlińska, Karolina Seweryn, Aleksandra Krasnodębska, Paula Betscher, Zofia Cieślińska, Katarzyna Kowol, Artur Wilczek, Maciej Trzciński, Katarzyna Dziewulska, Roman Roszko, Tomasz Bernaś, Jurgita Vaičenonienė, Danuta Roszko, Paweł Levchuk, Paweł Kowalski, Irena Prawdzic-Jankowska
/ Abstract
This paper describes the instruction dataset used to fine-tune a set of transformer-based large language models (LLMs) developed in the PLLuM (Polish Large Language Model) project. We present a functional typology of the organic, converted, and synthetic instructions used in PLLuM and share some observations about the implications of using human-authored versus synthetic instruction datasets in the linguistic adaptation of base LLMs. Additionally, we release the first representative subset of the PLLuM instruction corpus (PLLuMIC), which we believe to be useful in guiding and planning the development of similar datasets for other LLMs.