task_categories:question-answering task_categories:translation task_categories:summarization task_categories:text-generation task_categories:conversational size_categories:100K<n<1M language:en license:cc-by-4.0 code airoboros language merge gpt region:us
---
license: cc-by-4.0
task_categories:
- question-answering
- translation
- summarization
- text-generation
- conversational
language:
- en
tags:
- code
- airoboros
- language
- merge
- gpt
pretty_name: helix
size_categories:
- 100K<n<1M
---

# Helix Dataset for Questioning and Instructing (QI)

## Description
The Helix dataset is a specialized collection of data tailored for Questioning and Instructing (QI) tasks. It is created by merging all the Airoboros datasets and incorporating one RosettaCode dataset, with a primary focus on supporting QI research and applications.

## Dataset Details
- **Source Datasets**: Airoboros datasets (various sources), RosettaCode dataset
- **Merging Script**: The merging of these datasets was performed using the `bowie.py` script, which is included in this repository. The script facilitates the formatting and integration of the datasets to create the Helix dataset optimized for QI tasks.

## Usage
The Helix dataset is particularly suited for researchers and developers working on QI tasks, including:
- Developing QI systems that can understand and respond to natural language queries and instructions.
- Training and evaluating machine learning models for QI applications.
- Benchmarking QI algorithms and techniques.
- Investigating the intersection of natural language understanding and instructional responses.

## License
Please refer to the individual licenses of the source datasets for specific licensing information. Ensure compliance with the respective licenses when using the Helix dataset.

## Citation
If you use the Helix dataset for QI research or projects, please consider citing it using the appropriate citation format for each of the source datasets and the `bowie.py` script.

```
Marcus. 2023. Helix Dataset for Questioning and Instructing (QI). Helix. Self-published. https://huggingface.co/datasets/KaleidoSG/Helix
```

## Acknowledgments
We express our gratitude to the creators and maintainers of the Airoboros datasets and the RosettaCode dataset for their valuable contributions to this specialized dataset for Questioning and Instructing (QI) tasks.