metadata

license: cc-by-sa-4.0
size_categories:
  - 10B<n<100B

XLM-R-BERTić dataset

Composition and usage

This dataset contains 11.5 billion words and consists of the following splits:

macocu_hbs
hr_news
bswac
cc100_hr
cc100_sr
classla_sr
classla_hr
classla_bs
cnrwac
hrwac
mC4
riznica
srwac

The dataset was deduplicated with onion on the basis of 5-tuples of words with duplicate threshold set to 90%.

The entire dataset can be downloaded and used as follows:

import datasets
dict_of_datasets = datasets.load_dataset("classla/xlm-r-bertic-data")
full_dataset = datasets.concatenate_datasets([d for d in dict_of_datasets.values()])

A single split can be taken as well, but note that this means all the splits will be downloaded and generated, which can take a long time:

import datasets
riznica = datasets.load_dataset("classla/xlm-r-bertic-data", split="riznica")

To circumvent this one option is using streaming:

import datasets
riznica = datasets.load_dataset("classla/xlm-r-bertic-data", split="riznica", streaming=True)
for i in riznica.take(2):
    print(i)
# Output:
# {'text': 'PRAGMATIČARI DOGMATI SANJARI'}
# {'text': 'Ivica Župan'}