cnmoro/Mistral-7B-Portuguese
cnmoro/Mistral-7B-Portuguese is a 7 billion parameter language model, fine-tuned from mistralai/Mistral-7B-Instruct-v0.2, specifically optimized for performance in the Portuguese language. It utilizes a 4096-token context window and was trained using Unsloth on an instruction-based Portuguese dataset. This model aims to improve instruction-following capabilities and general language understanding for Portuguese applications.
Loading preview...
Overview
cnmoro/Mistral-7B-Portuguese is a 7-billion parameter instruction-tuned model, building upon the mistralai/Mistral-7B-Instruct-v0.2 architecture. Its primary goal is to enhance performance and instruction-following capabilities specifically for the Portuguese language. The model was fine-tuned using Unsloth on a dedicated Portuguese instruction dataset.
Key Capabilities & Performance
This model demonstrates strong performance across various Portuguese language tasks, as evaluated on the Open Portuguese LLM Leaderboard. It achieves an average score of 64.7, with notable results in:
- Assin2 RTE: 90.31
- Assin2 STS: 76.55
- HateBR Binary: 79.21
- PT Hate Speech Binary: 68.87
Use Cases
- Portuguese-centric applications: Ideal for chatbots, content generation, and instruction-following tasks requiring high proficiency in Portuguese.
- Sentiment analysis and text classification: Strong scores in Hate Speech and tweetSentBR indicate suitability for these tasks.
- Educational and legal contexts: Performance on OAB Exams and ENEM Challenge suggests potential for applications in these domains, though further evaluation may be beneficial.