mamed0v/dolly-15k-turkmen

Turkmen Dolly 15k Dataset

Overview

This dataset is a Turkmen translation of the original Dolly 15k dataset. The Dolly dataset is a publicly available instruction-following dataset created by Databricks, containing 15,000 high-quality human-generated prompt-response pairs. This Turkmen version aims to extend the accessibility of instruction-following datasets to the Turkmen language community.

Dataset Details

• —Original Dataset: Dolly 15k
• —Language: Turkmen
• —Number of Samples: 15,000
• —Types of Tasks: Various, including open-ended generation, classification, extraction, and more
• —Translation Method: Google Translate

File Format

The dataset is provided in JSONL (JSON Lines) format. Each line in the file represents a single JSON object with the following structure:

{
  "instruction": "Original instruction in English",
  "context": "Original context in English (if applicable)",
  "response": "Original response in English",
  "category": "Category of the task",
  "instruction_tk": "Instruction translated to Turkmen",
  "context_tk": "Context translated to Turkmen (if applicable)",
  "response_tk": "Response translated to Turkmen"
}

Example:

{
  "instruction": "In the series A Song of Ice and Fire, who is the founder of House Casterly?",
  "context": "",
  "response": "Corlos, son of Caster",
  "category": "open_qa",
  "instruction_tk": "\"Buz we ot aýdymy\" seriýasynda \"House Casterly\" -ny esaslandyryjy kim?",
  "context_tk": "",
  "response_tk": "Karlos, Kasteriň ogly"
}

Acknowledgments

• —Original Dolly 15k dataset creators: Databricks
• —Translation: Google Translate

Contact

For questions or issues regarding this dataset, please contact:

• —Telegram: @gargamelix
• —Email: 31mb41@gmail.com
• —GitHub: github.com/mamed0v

Disclaimer

The translations in this dataset were performed using Google Translate. While this approach allows for rapid translation of a large dataset, users should be aware that there might be inaccuracies, mistranslations, or loss of nuance, especially for complex or domain-specific content. Exercise caution when using this dataset for tasks requiring high precision in language understanding or generation.