PORTULAN/gervasio-7b-portuguese-ptbr-decoder
PORTULAN/gervasio-7b-portuguese-ptbr-decoder is a 7 billion parameter decoder-only language model developed by the NLX-Natural Language and Speech Group at the University of Lisbon. Based on the LLaMA-2 architecture, it is specifically fine-tuned for the Brazilian Portuguese variant, excelling in tasks like textual entailment and semantic similarity in Portuguese. This model is designed for generative AI applications requiring strong performance in Brazilian Portuguese.
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Gervásio 7B PTBR Decoder: Brazilian Portuguese LLM
This model, Gervásio 7B PTBR, is a 7 billion parameter decoder-only language model developed by the NLX-Natural Language and Speech Group at the University of Lisbon. It is based on the LLaMA-2 architecture and has been specifically fine-tuned for the Brazilian Portuguese (PTBR) variant. While this specific version is deprecated in favor of gervasio-8b-portuguese-ptpt-decoder, it represents an important development for Portuguese language AI.
Key Capabilities & Training
- Brazilian Portuguese Focus: Optimized for tasks in Brazilian Portuguese, showing strong performance in textual entailment and semantic similarity compared to English LLaMA-2 models.
- LLaMA-2 Base: Built upon the robust LLaMA-2 7B model, leveraging its Transformer architecture.
- Instruction Fine-tuning: Improved through additional training on Portuguese instruction datasets, specifically
extraGLUE-Instruct, which includes machine-translated GLUE and SuperGLUE tasks. - Open License: Distributed under an MIT license, allowing for free use in research and commercial applications.
Performance Highlights
Benchmarking against LLaMA-2 (English) and LLaMA-2 Chat (English) on Portuguese datasets, Gervásio 7B PTBR demonstrated superior performance in:
- MRPC (F1): 0.7822 (vs. 0.0369 for LLaMA-2 English)
- RTE (F1): 0.8321 (vs. 0.0516 for LLaMA-2 English)
- ASSIN2 RTE (F1): 0.7469
- ASSIN2 STS (Pearson): 0.2136
Use Cases
This model is suitable for generative AI applications requiring high-quality text generation and understanding in Brazilian Portuguese, particularly for tasks involving semantic analysis and inference. Its design allows it to run on consumer-grade hardware.