Polygl0t/Tucano2-qwen-3.7B-Instruct
Polygl0t/Tucano2-qwen-3.7B-Instruct is a 3.76 billion parameter instruction-tuned Portuguese language model built on a Qwen3 Transformer architecture. Developed by Polygl0t, it was trained using supervised fine-tuning and Anchored Preference Optimization on specific Portuguese datasets. This model excels at tasks such as retrieval-augmented generation, function calling, summarization, and structured output generation, making it suitable for research and development in Portuguese language modeling.
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Tucano2-qwen-3.7B-Instruct: A Specialized Portuguese LLM
Tucano2-qwen-3.7B-Instruct is a 3.76 billion parameter instruction-tuned model developed by Polygl0t, specifically designed for the Portuguese language. Built upon a Qwen3 Transformer architecture, it leverages a combination of supervised fine-tuning (SFT) and Anchored Preference Optimization (APO) using the Polygl0t/gigaverbo-v2-sft and Polygl0t/gigaverbo-v2-preferences datasets.
Key Capabilities
- Strong Portuguese Performance: Delivers robust results across various Portuguese benchmarks.
- Versatile Task Handling: Supports retrieval-augmented generation, function calling, tool use, summarization, and structured output generation.
- Open and Reproducible: All datasets, source code, and training recipes for the Tucano2 series are fully open and available.
Good for
- Portuguese Language Research: Serves as a foundational model for R&D in Portuguese NLP.
- Fine-tuning and Adaptation: Suitable for further fine-tuning for specific deployment scenarios under the Apache 2.0 license.
- Benchmarking: Offers competitive performance against other 3-4B parameter chat models in Portuguese, particularly in Knowledge & Reasoning tasks, where it achieves a Normalized Performance Metric (NPM) of 56.22, surpassing models like Jurema-7B and Qwen2.5-3B-Instruct in this category.