Update README.md

README.md

@@ -94,9 +94,42 @@ size_categories:
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 # Polygl0t Tokenizers
 
-This dataset contains several subsets for training multilingual tokenizers. All samples on their respective datasets have been filtered for their educational content (e.g., all 5 scores from FineWeb-Edu in the case of English).
+## Table of Contents
 
-The `code` subset is a mixture of 36 programming languages.
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Subsets and Splits](#subsets-and-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Source Data](#source-data)
+- [Additional Information](#additional-information)
+  - [Dataset Maintainers](#dataset-maintainers)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Acknowledgments](#acknowledgments)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://huggingface.co/datasets/Polygl0t/tokenizers
+- **Repository:** https://huggingface.co/datasets/Polygl0t/tokenizers
+- **Point of Contact:** [Polyg0t](mailto:kluge@uni-bonn.de)
+
+### Dataset Summary
+
+This dataset contains several subsets for training multilingual tokenizers. Every subset possesses a collection of curated text samples in different languages. 
+
+### Supported Tasks and Leaderboards
+
+This dataset can be used for the task of text generation, specifically for training and evaluating tokenizers in multiple languages.
+
+### Languages
+
+Hindi, Bengali, English, Portuguese, and Code (a mixture of 36 programming languages).
 
 <details>
 <summary><b>All programming languages</b></summary>
@@ -105,4 +138,68 @@ The `code` subset is a mixture of 36 programming languages.
  </code>
 </details>
 
-The `txt` files (e.g., [`hindi_test.txt`](hindi_test.txt)) are for testing purposes.
+## Dataset Structure
+
+### Data Instances
+
+The dataset consists of the following features:
+
+- **text:** a string of text in the respective language of the subset.
+
+### Data Fields
+
+```json
+{
+  "text": "Olá, como vai você?"
+}
+```
+
+### Subsets and Splits
+
+The dataset includes the following subsets:
+
+- **Portuguese:** This subset contains 2,000,000 text samples in Portuguese.
+- **Hindi:** This subset contains 2,000,000 text samples in Hindi.
+- **Bengali:** This subset contains 2,000,000 text samples in Bengali
+- **English:** This subset contains 2,000,000 text samples in English.
+- **Code:** This subset contains 975,000 text samples in various programming languages.
+
+The `txt` files (e.g., [`hindi_test.txt`](hindi_test.txt)) are for testing/evaluation purposes.
+
+### Dataset Creation
+
+### Source Data
+
+- **Bengali:** The Bengali text samples were sourced from [Polygl0t/bengali-corpus](https://huggingface.co/datasets/Polygl0t/bengali-corpus).
+- **English:** The English text samples were sourced from [HuggingFaceFW/fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu).
+- **Hindi:** The Hindi text samples were sourced from [Polygl0t/hindi-corpus](https://huggingface.co/datasets/Polygl0t/hindi-corpus).
+- **Portuguese:** The Portuguese text samples were sourced from [TucanoBR/GigaVerbo](https://huggingface.co/datasets/TucanoBR/GigaVerbo).
+- **Code:** The code samples were sourced from [bigcode/starcoderdata](https://huggingface.co/datasets/bigcode/starcoderdata).
+
+## Additional Information
+
+### Dataset Maintainers
+
+- [Nicholas Kluge Corrêa](mailto:kluge@uni-bonn.de).
+- [Aniket Sen](mailto:sen@hiskp.uni-bonn.de).
+
+### Licensing Information
+
+Please refer to the individual licenses of the source datasets used to create this corpus, as listed in the "Source Data" section above. The combined dataset does not have a single unified license, and users should ensure compliance with the terms of each source dataset when utilizing this corpus.
+
+### Citation Information
+
+```latex
+
+```
+
+### Acknowledgments
+
+Polyglot is a project funded by the Federal Ministry of Education and Research (BMBF) and the Ministry of Culture and Science of the State of North Rhine-Westphalia (MWK) as part of TRA Sustainable Futures (University of Bonn) and the Excellence Strategy of the federal and state governments.
+
+We also gratefully acknowledge the granted access to the [Marvin cluster](https://www.hpc.uni-bonn.de/en/systems/marvin) hosted by [University of Bonn](https://www.uni-bonn.de/en) along with the support provided by its High Performance Computing & Analytics Lab.
+
+
+### Contributions
+
+If you want to contribute, contact us at [polyglot@uni-bonn.de](mailto:polyglot@uni-bonn.de)!