opus-mt-en-sq
| Property | Value |
|---|---|
| Model Type | Neural Machine Translation |
| Architecture | Transformer-align |
| Developer | Helsinki-NLP |
| BLEU Score | 46.5 (Tatoeba test set) |
| Source Language | English |
| Target Language | Albanian |
What is opus-mt-en-sq?
opus-mt-en-sq is a specialized neural machine translation model developed by Helsinki-NLP for translating text from English to Albanian. The model utilizes the transformer-align architecture and has demonstrated impressive performance with a BLEU score of 46.5 on the Tatoeba test set.
Implementation Details
The model employs a transformer-based architecture with alignment capabilities, trained on the OPUS dataset. Pre-processing includes normalization and SentencePiece tokenization, ensuring optimal handling of both English and Albanian text.
- Built on transformer-align architecture
- Utilizes SentencePiece tokenization
- Trained on OPUS dataset
- Achieves 0.669 chr-F score
Core Capabilities
- High-quality English to Albanian translation
- Handles various text formats and styles
- Optimized for production deployment
- Suitable for both academic and commercial applications
Frequently Asked Questions
Q: What makes this model unique?
This model specifically focuses on English-to-Albanian translation, achieving a remarkable BLEU score of 46.5 on the Tatoeba test set. Its transformer-align architecture and specialized pre-processing make it particularly effective for this language pair.
Q: What are the recommended use cases?
The model is ideal for applications requiring English to Albanian translation, including content localization, document translation, and automated translation services. Its high BLEU and chr-F scores make it suitable for professional translation tasks.
