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---
license: mit
---
CoreXDataSet/README.md
```md
# CoreXDataSet
## Overview
CoreXDataSet is a comprehensive multi-modal dataset curated specifically for training and evaluating the OmniCoreX AI model — the ultimate AI brain designed for integrating infinite knowledge streams with adaptive reasoning and real-time decision-making capabilities.
This dataset includes diverse data modalities such as text, images, sensor readings, audio, and more, enabling OmniCoreX to learn cross-modal representations and perform advanced multi-stream reasoning across varied real-world scenarios.
---
## Contents
- **Text**: Rich corpora including encyclopedic knowledge, technical documents, and conversational data.
- **Images**: High-resolution images covering a wide variety of domains such as nature, urban scenes, and technology.
- **Sensor Data**: Time-series sensor recordings from IoT devices, robotics, and mobile platforms.
- **Audio**: Speech and environmental audio clips for audio pattern understanding and integration.
- **Labels/Annotations**: Metadata and annotations required for supervised learning tasks.
---
## Dataset Structure
```
CoreXDataSet/
├── metadata.json # Descriptions and references for dataset samples
├── text/ # Directory containing text files or JSON documents
├── images/ # Directory containing images in jpeg/png format
├── sensors/ # CSV or binary files for sensor data sequences
├── audio/ # Audio clips in WAV/MP3 format
└── annotations/ # Optional annotations for supervised tasks
```
---
## License
CoreXDataSet is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). Please review the LICENSE file for more details.
---
## Usage
### Accessing the Data
Download and extract the CoreXDataSet archive. Use the provided metadata file to index and load samples efficiently using the OmniCoreX data loader utilities.
### Integration
CoreXDataSet is designed for seamless integration with the OmniCoreX training pipelines and model architectures. Utilize the dataset modules and data loaders included within the OmniCoreX repository.
---
## Citation
If you use CoreXDataSet in your research, please cite it as:
```
@dataset{corexdataset2024,
title={CoreXDataSet: Multi-Modal Dataset for OmniCoreX AI},
author={Kosasih, Team},
year={2024},
publisher={OmniCoreX Initiative},
url={https://github.com/KOSASIH/CoreXDataSet}
}
```
---
## Contribution
We welcome contributions to enhance CoreXDataSet with new modalities, expanded annotations, and improved quality. Please see the CONTRIBUTING.md file in the dataset repository for guidelines.
---
## Contact
For inquiries, questions, or support related to CoreXDataSet:
- Email: support@omnicorex.ai
- GitHub: https://github.com/KOSASIH/CoreXDataSet
---
Empower your AI research with the rich and diverse CoreXDataSet — training the next generation AI brain.
``` |