README.md

metadata

language:
  - sr
  - hr
  - sl
  - bs
pretty_name: ZNANJE
size_categories:
  - 1B<n<10B
configs:
  - config_name: default
    data_files:
      - split: train
        path:
          - '*_sr.jsonl'
          - '*_hr.jsonl'
          - '*_cnr.jsonl'
          - '*_bs.jsonl'
      - split: sr
        path: '*_sr.jsonl'
      - split: hr
        path: '*_hr.jsonl'
      - split: si
        path: '*_si.jsonl'
      - split: bs
        path: '*_bs.jsonl'
      - split: sve
        path:
          - '*_sr.jsonl'
          - '*_hr.jsonl'
          - '*_cnr.jsonl'
          - '*_bs.jsonl'
          - '*_si.jsonl'
task_categories:
  - text-generation
license: cc-by-sa-4.0

Skup naučnih radova na Južnoslovenskim jezicima Visoko-kvalitetan skup raznovrsnih naučnih publikacija Neophodan za obučavanje kvalitetnih jezičkih modela za južnoslovenske jezike. Ukupno ? dokumenata, ukupno sa preko ? reči. Svaka JSON linija predstavlja jednu publikaciju. Unutar svakog dokumenta su obeležene rečenice i paragrafi.	Set of South Slavic Scientific Research publications Highly curated, High-qualityand diverse scientific publications. Necessary for training quality language models for Serbian. A total of ? documents containing over ? words. Each JSON line represents one publication. All documents are paragraph and sentence-delimited.
Број докумената Doc. count Број реченица Sent. count Број речи Word count Удео Share Korpus S.T.A.R.S. 🇷🇸 23,340 27,760,829 704,000,000 81.9% DABAR 🇭🇷 108,786 53,369,657 1,214,000,000 Open Science Slovenia 🇸🇮 🇷🇸 🇭🇷 🇧🇦 176 113,339 2,694,331 Укупно Total 23,340 27,760,829 704,000,000 100%

from datasets import load_dataset
dataset = load_dataset("procesaur/ZNANJE")

Editor

Mihailo Škorić

@procesaur

Citation:

@article{skoric24korpusi,
  author    = {\vSkori\'c, Mihailo and Jankovi\'c, Nikola},
  title     = {New Textual Corpora for Serbian Language Modeling},
  journal   = {Infotheca},
  volume    = {24},
  issue     = {1},
  year      = {2024},
  publisher = {Zajednica biblioteka univerziteta u Srbiji, Beograd},
  url       = {https://arxiv.org/abs/2405.09250}
}

Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA.

This research was supported by the Science Fund of the Republic of Serbia, #7276, Text Embeddings - Serbian Language Applications - TESLA.