|
|
---
|
|
|
title: README
|
|
|
emoji: ⚡
|
|
|
colorFrom: green
|
|
|
colorTo: purple
|
|
|
sdk: static
|
|
|
pinned: false
|
|
|
license: cc-by-4.0
|
|
|
thumbnail: >-
|
|
|
https://cdn-uploads.huggingface.co/production/uploads/65b36226d1164871bea7b44e/i366z3fgsPHioZiMGR4fG.png
|
|
|
short_description: Small Enough to Care Big Enough to Success
|
|
|
---
|
|
|
|
|
|
# RSA Team |
|
|
|
|
|
## About Us |
|
|
|
|
|
RSA Team is an AI/ML research and development organization focused on advancing natural language processing capabilities for underrepresented languages, particularly those in the Balkan region. We build high-quality datasets, develop language models, and create tools that bridge the gap between cutting-edge AI technology and linguistic diversity. |
|
|
|
|
|
## Our Mission |
|
|
|
|
|
We are committed to democratizing AI technology by: |
|
|
|
|
|
- **Building Language Resources**: Creating comprehensive datasets for Serbian, Bosnian, Croatian, and other Balkan languages |
|
|
- **Advancing NLP Research**: Developing state-of-the-art models tailored for multilingual and low-resource language scenarios |
|
|
- **Open Source Contribution**: Sharing our work with the global AI community to foster collaboration and innovation |
|
|
- **Practical Applications**: Bridging research and real-world applications in healthcare, document processing, and enterprise systems |
|
|
|
|
|
## Focus Areas |
|
|
|
|
|
### Natural Language Processing |
|
|
We specialize in NLP tasks including text classification, named entity recognition, machine translation, and sentiment analysis for Balkan languages. |
|
|
|
|
|
### Multilingual AI Models |
|
|
Our work emphasizes creating models that perform well across multiple related languages while preserving linguistic nuances and cultural context. |
|
|
|
|
|
### Healthcare Technology |
|
|
We develop AI-powered solutions for healthcare systems, including FHIR-compliant data processing, medical document analysis, and clinical decision support tools. |
|
|
|
|
|
### Document Intelligence |
|
|
Advanced OCR, information extraction, and document understanding systems with particular focus on multilingual document processing. |
|
|
|
|
|
## Our Datasets |
|
|
|
|
|
We curate and publish high-quality datasets designed for: |
|
|
- Training and fine-tuning large language models |
|
|
- Benchmarking NLP systems on Balkan languages |
|
|
- Research in multilingual and cross-lingual transfer learning |
|
|
- Building practical AI applications with strong language support |
|
|
|
|
|
Each dataset includes comprehensive documentation, usage examples, and integration guidelines for popular ML frameworks. |
|
|
|
|
|
## Technology Stack |
|
|
|
|
|
Our projects leverage modern AI/ML technologies including: |
|
|
- Transformers and large language models |
|
|
- PyTorch and TensorFlow |
|
|
- Hugging Face ecosystem |
|
|
- FHIR standards for healthcare interoperability |
|
|
- Full-stack development (Java, Python, Flutter, Oracle) |
|
|
|
|
|
## Community & Collaboration |
|
|
|
|
|
We believe in open collaboration and knowledge sharing. Whether you're a researcher, developer, or organization working on similar challenges, we welcome: |
|
|
|
|
|
- Dataset contributions and improvements |
|
|
- Model fine-tuning and evaluation |
|
|
- Bug reports and feature requests |
|
|
- Research collaborations |
|
|
- Use cases and application feedback |
|
|
|
|
|
## Contact |
|
|
|
|
|
- Website: [https://rsateam.com](https://rsateam.com) |
|
|
- GitHub: [@rsadevteam](https://github.com/rsadevteam) |
|
|
- Hugging Face: [@rsateam](https://huggingface.co/rsateam) |
|
|
|
|
|
## License |
|
|
|
|
|
Unless otherwise specified, our datasets and models are released under permissive licenses to encourage both academic research and commercial applications. Please refer to individual repository licenses for specific terms. |
|
|
|
|
|
## Citation |
|
|
|
|
|
If you use our resources in your research or applications, please cite: |
|
|
```bibtex |
|
|
@misc{rsateam2026, |
|
|
author = {RSA Team}, |
|
|
title = {Balkan Language Resources and Models}, |
|
|
year = {2026}, |
|
|
publisher = {Hugging Face}, |
|
|
howpublished = {\url{https://huggingface.co/rsateam}} |
|
|
} |
|
|
``` |
|
|
|
|
|
--- |
|
|
|
|
|
*Building bridges between languages and AI, one dataset at a time.* |
