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README.md

@@ -1,41 +1,77 @@
+
 ---
-license: mit
-tags:
-- self-supervised-pretraining
-language:
+language: 
 - ind
 - jav
 - sun
+- mya
+- lao
+- khm
+- tgl
+- vie
+- tha
+- zlm
+pretty_name: Cc100
+task_categories: 
+- self-supervised-pretraining
+tags: 
+- self-supervised-pretraining
 ---
 
-# cc100
-
-This corpus is an attempt to recreate the dataset used for training
-
+        This corpus is an attempt to recreate the dataset used for training
         XLM-R. This corpus comprises of monolingual data for 100+ languages and
-
         also includes data for romanized languages (indicated by *_rom). This
-
         was constructed using the urls and paragraph indices provided by the
-
         CC-Net repository by processing January-December 2018 Commoncrawl
-
         snapshots. Each file comprises of documents separated by
-
         double-newlines and paragraphs within the same document separated by a
-
         newline. The data is generated using the open source CC-Net repository.
-
         No claims of intellectual property are made on the work of preparation
-
         of the corpus.
 
+
+## Languages
+
+ind, jav, sun, mya, mya_zaw, lao, khm, tgl, vie, tha, zlm
+
+## Supported Tasks
+
+Self Supervised Pretraining
+    
 ## Dataset Usage
+### Using `datasets` library
+```
+    from datasets import load_dataset
+    dset = datasets.load_dataset("SEACrowd/cc100", trust_remote_code=True)
+```
+### Using `seacrowd` library
+```import seacrowd as sc
+# Load the dataset using the default config
+    dset = sc.load_dataset("cc100", schema="seacrowd")
+# Check all available subsets (config names) of the dataset
+    print(sc.available_config_names("cc100"))
+# 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).
+    
 
-Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
+## Dataset Homepage
+
+[https://data.statmt.org/cc-100/](https://data.statmt.org/cc-100/)
+
+## Dataset Version
+
+Source: 2018.12.01. SEACrowd: 2024.06.20.
+
+## Dataset License
+
+MIT
 
 ## Citation
 
+If you are using the **Cc100** dataloader in your work, please cite the following:
 ```
 @inproceedings{conneau-etal-2020-unsupervised,
     title = "Unsupervised Cross-lingual Representation Learning at Scale",
@@ -105,16 +141,14 @@ Run `pip install nusacrowd` before loading the dataset through HuggingFace's `lo
     language = "English",
     ISBN = "979-10-95546-34-4",
 }
-```
-
-## License
-
-MIT
-
-## Homepage
 
-[https://data.statmt.org/cc-100/](https://data.statmt.org/cc-100/)
 
-### NusaCatalogue
+@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}
+}
 
-For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)
+```