split
Datasets
All datasets matching “split”github-code-2025-language-split
📜 Source Data & Attribution
This dataset is a processed derivative of nick007x/github-code-2025.
Origination
The original data was aggregated by nick007x from public GitHub repositories. We have retained the original content, file paths, and metadata while restructuring the format for easier consumption by language-specific models.
Processing Steps
To create this dataset, we performed the following processing on the source data:
Language… See the full description on the dataset page: https://huggingface.co/datasets/hasankursun/github-code-2025-language-split.aya_collection_language_split
This is a re-upload of the aya_collection, and only differs in the structure of upload. While the original aya_collection is structured by folders split according to dataset name, this dataset is split by language. We recommend you use this version of the dataset if you are only interested in downloading all of the Aya collection for a single or smaller set of languages.
Dataset Summary
The Aya Collection is a massive multilingual collection consisting of 513 million instances of… See the full description on the dataset page: https://huggingface.co/datasets/CohereLabs/aya_collection_language_split.the-pile-splitted
Dataset description
The pile is an 800GB dataset of english text
designed by EleutherAI to train large-scale language models. The original version of
the dataset can be found here.
The dataset is divided into 22 smaller high-quality datasets. For more information
each of them, please refer to the datasheet for the pile.
However, the current version of the dataset, available on the Hub, is not splitted accordingly.
We had to solve this problem in order to improve the user… See the full description on the dataset page: https://huggingface.co/datasets/ArmelR/the-pile-splitted.muri-it-language-split
MURI-IT: Multilingual Instruction Tuning Dataset for 200 Languages via Multilingual Reverse Instructions
MURI-IT is a large-scale multilingual instruction tuning dataset containing 2.2 million instruction-output pairs across 200 languages. It is designed to address the challenges of instruction tuning in low-resource languages with Multilingual Reverse Instructions (MURI), which ensures that the output is human-written, high-quality, and authentic to the cultural and linguistic… See the full description on the dataset page: https://huggingface.co/datasets/akoksal/muri-it-language-split.traditionnals_arabic_shoes_splitimagefolder_with_metadata_no_splits