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README.md

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+
+---
+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}
+}
+
+```