malhajar/Mistral-7B-v0.2-meditron-turkish
malhajar/Mistral-7B-v0.2-meditron-turkish is a 7 billion parameter Mistral-based model, fine-tuned by Mohamad Alhajar using the Freeze technique on a Turkish Meditron dataset. This model specializes in providing medical information in both Turkish and English, making it suitable for healthcare-related natural language processing tasks. It leverages the Mistral-7B-Instruct-v0.2 architecture, optimized for domain-specific medical queries.
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Overview
malhajar/Mistral-7B-v0.2-meditron-turkish is a 7 billion parameter language model developed by Mohamad Alhajar. It is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2, specifically adapted for medical contexts. The model was trained using the Freeze technique on the malhajar/meditron-tr dataset, which focuses on Turkish medical information.
Key Capabilities
- Medical Information Retrieval: Excels at answering questions and providing information on various explicit medical ideas.
- Bilingual Support: Capable of generating responses in both Turkish and English, catering to a broader user base in medical domains.
- Domain-Specific Fine-tuning: Optimized for medical terminology and concepts through specialized training on a Meditron dataset.
Performance
Evaluated on the Open LLM Leaderboard, the model achieved an average score of 63.34. Notable benchmark results include:
- HellaSwag (10-Shot): 81.79
- Winogrande (5-shot): 76.24
- TruthfulQA (0-shot): 66.19
- MMLU (5-Shot): 60.35
Use Cases
This model is particularly well-suited for applications requiring accurate medical information in Turkish and English, such as:
- Medical question-answering systems.
- Healthcare chatbots.
- Assisting medical professionals or students with information retrieval.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.