README.md

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

To circumvent this one option is using streaming:

```python
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'}
```
Read more on streaming [here](https://huggingface.co/docs/datasets/stream).