Slovene instruction-following dataset for large language models GaMS-Instruct-GEN 1.0

  Authors

Vreš, Domen ; et al.show everyone

Vreš, Domen ; Arčon, Tjaša ; Čibej, Jaka ; Robnik-Šikonja, Marko ; Krek, Simon ; Gabrovšek, Dejan ; Ježovnik, Janoš ; Kastelic, Maja ; Krvina, Domen ; Ledinek, Nina ; Michelizza, Mija ; Perdih, Andrej ; Petric Žižić, Špela ; Trojar, Mitja

  Item identifier

http://hdl.handle.net/11356/1971

 Project URL

https://www.cjvt.si/povejmo/en/project/

 Date issued

2024-09-25

 Type

corpus, text

 Size

6832 units

 Language(s)

Slovenian

 Description

GaMS-Instruct-GEN is an instruction-following dataset designed to fine-tune Slovene large language models to follow instructions. It consists of pairs of prompts and responses, some of which contain an additional input field. The dataset was generated automatically using GPT-4 by using 225 manually compiled seed prompts from SelfInstruct (Wang et al. 2022), an instruction-following dataset for English (https://huggingface.co/datasets/yizhongw/self_instruct). The seed prompts were manually translated into Slovene (see "seed_tasks_sl.jsonl") and used as part of a prompt to generate additional similar examples (see 00README.txt for more details). The automatically generated examples were manually validated by 9 annotators (linguists). Version 1.0 contains only prompt-response pairs that are adequately formatted and free of LLM-hallucinations. Most of the prompt-response pairs deal with general topics (e.g. essay writing, event organization, text corrections, creative tasks), while some deal with Slovene-specific topics (e.g. planning trips around Slovenia, prompts referring to Slovene literature or culture).

 Publisher

Faculty of Computer and Information Science, University of Ljubljana

 Acknowledgement

ARRS (Slovenian Research Agency) P6-0411 "Language Resources and Technologies for Slovene"

ARIS (Slovenian Research and Innovation Agency) NOO "PoVeJMo research project (Adaptive Natural Language Processing with Large Language Models)"

 Subject(s)

large language models instruction following dataset

 Collection(s)

CLARIN.SI data & tools

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