Hugging Face Overview
Teuta: Bilingual Instruction-Tuned Language Model
Teuta, developed by LTS-VVE, is a 3.2 billion parameter instruction-tuned language model built upon the meta-llama/Llama-3.2-3B base. Its primary focus is bilingual question answering and instruction-following in both Albanian (sq) and English (en), making it particularly valuable for multilingual applications and supporting under-resourced languages.
Key Capabilities & Features
- Bilingual Proficiency: Optimized for instruction-following and question answering in Albanian and English.
- Diverse Domain Knowledge: Fine-tuned on a broad spectrum of subjects including mathematics, philosophy, chemistry, biology, code (with a specific emphasis on Rust), psychology, and climate science.
- Instruction Following: Designed to handle various instructional prompts, from academic queries to more open-ended tasks.
- Generalization: Leverages both synthetic and real datasets to enhance its ability to generalize across technical and non-technical domains.
Ideal Use Cases
- Research: Suitable for exploring language model capabilities in bilingual contexts.
- Educational Tools: Can be integrated into tools for learning or information retrieval in Albanian and English.
- Domain-Specific Applications: Effective for applications requiring specialized knowledge in the aforementioned scientific and technical fields.
- Under-resourced Language Support: Particularly strong for applications focusing on the Albanian language.
Important Considerations
- The model's training data includes sensitive content (e.g., mental health, therapy, philosophical questions).
- Outputs are not guaranteed to be factual or safe, requiring careful consideration for sensitive applications.