README.md

---
license: cc0-1.0
language: 
- ind
- zlm
- tha
- mya
- fil
- vie
pretty_name: Hplt
task_categories: 
- self-supervised-pretraining
tags: 
- self-supervised-pretraining
---

The dataset is part of the High Performance Language Technologies project
(HPLT), a 3-year EU-funded project started in September 2022. HPLT derives
monolingual and bilingual datasets from the Internet Archive and CommonCrawl and
builds efficient and solid machine translation (MT) as well as large language
models (LLMs). HPLT aims at providing free, sustainable and reusable datasets,
models and workflows at scale using high-performance computing (HPC).


## Languages

ind, zlm, tha, mya, fil, vie

## Supported Tasks

Self Supervised Pretraining

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/hplt", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("hplt", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("hplt"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
```

More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).


## Dataset Homepage

[https://hplt-project.org/datasets/v1.2](https://hplt-project.org/datasets/v1.2)

## Dataset Version

Source: 1.2.0. SEACrowd: 2024.06.20.

## Dataset License

Creative Commons Zero v1.0 Universal (cc0-1.0)

## Citation

If you are using the **Hplt** dataloader in your work, please cite the following:
```
\
@inproceedings{aulamo-etal-2023-hplt,
    title = "{HPLT}: High Performance Language Technologies",
    author = {Aulamo, Mikko  and
        Bogoychev, Nikolay  and
        Ji, Shaoxiong  and
        Nail, Graeme  and
        Ram{\'\i}rez-S{\'a}nchez, Gema  and
        Tiedemann, J{\"o}rg  and
        van der Linde, Jelmer  and
        Zaragoza, Jaume},
    editor = "Nurminen, Mary  and
        Brenner, Judith  and
        Koponen, Maarit  and
        Latomaa, Sirkku  and
        Mikhailov, Mikhail  and
        Schierl, Frederike  and
        Ranasinghe, Tharindu  and
        Vanmassenhove, Eva  and
        Vidal, Sergi Alvarez  and
        Aranberri, Nora  and
        Nunziatini, Mara  and
        Escart{\'\i}n, Carla Parra  and
        Forcada, Mikel  and
        Popovic, Maja  and
        Scarton, Carolina  and
        Moniz, Helena",
    booktitle = "Proceedings of the 24th Annual Conference of the European
    Association for Machine Translation",
    month = jun,
    year = "2023",
    address = "Tampere, Finland",
    publisher = "European Association for Machine Translation",
    url = "https://aclanthology.org/2023.eamt-1.61",
    pages = "517--518",

    abstract = "We describe the High Performance Language Technologies project
    (HPLT), a 3-year EU-funded project started in September 2022. HPLT will
    build a space combining petabytes of natural language data with large-scale
    model training. It will derive monolingual and bilingual datasets from the
    Internet Archive and CommonCrawl and build efficient and solid machine
    translation (MT) as well as large language models (LLMs). HPLT aims at
    providing free, sustainable and reusable datasets, models and workflows at
    scale using high-performance computing (HPC).",
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}

```