Unbabel/Tower-Plus-2B: Multilingual LLM for Translation and Beyond
Unbabel's Tower-Plus-2B is a 2.6 billion parameter model, leveraging the Gemma 2 2B architecture. It has undergone a rigorous training regimen including Continuous Pretraining (CPT), Instruction Tuning (IT), Weighted Preference Optimization (WPO), and GRPO with verifiable rewards. A key differentiator is its extensive training on parallel and multilingual data, covering 22 languages, making it a leading multilingual LLM under 3 billion parameters.
Key Capabilities
- Exceptional Multilingual Translation: Specifically strong in machine translation across its supported languages.
- General Multilingual Instruction Following: Capable of handling various instruction-following tasks in multiple languages, including reasoning and code instructions.
- Multilingual Synthetic Data Generation: Effective for creating synthetic data by translating instructions and answers or generating instructions from seed documents.
- Broad Language Support: Covers 22 languages including German, Spanish, French, Italian, Korean, Dutch, Russian, English, Portuguese (Portugal/Brazilian), Chinese (Simplified/Traditional), Czech, Ukrainian, Hindi, Icelandic, Japanese, Polish, Swedish, Hungarian, Romanian, Danish, Norwegian, and Finnish.
Good For
- Developers requiring a compact yet powerful multilingual model for translation tasks.
- Applications needing robust multilingual instruction following.
- Generating high-quality multilingual synthetic data for various NLP tasks.
This model is licensed under CC-BY-NC-4.0 and supports an 8192-token context window.