Recurv Medical Llama
The Recurv-Medical-Llama model is a fine-tuned version of Meta's LLaMa 3.1 8B, developed to provide precise and contextual assistance for healthcare professionals and researchers. This model excels in answering medical queries, assisting in anamnesis, and generating detailed explanations tailored for medical scenarios, leveraging state-of-the-art instruction tuning techniques.
(Knowledge cut-off date: 22th January, 2025)
🎯 Key Features
Optimized for medical-specific queries across various specialties.
Fine-tuned for clinical and research-oriented workflows.
Lightweight parameter-efficient fine-tuning with LoRA (Low-Rank Adaptation).
Multi-turn conversation support for context-rich interactions.
Generates comprehensive answers and evidence-based suggestions.
🚀 Model Card
Parameter
Details
Base Model
Meta LLaMa 3.1 8B
Fine-Tuning Framework
LoRA
Dataset Size
67,299 high-quality Q&A pairs
Context Length
4,096 tokens
Training Steps
100,000
Model Size
8 billion parameters
📊 Model Architecture
Dataset Sources
The dataset comprises high-quality Q&A pairs curated from medical textbooks, research papers, and clinical guidelines.
PubMed
Extracted insights from open-access medical research.
Clinical Guidelines
Data sourced from WHO, CDC, and specialty-specific guidelines.
EHR-Simulated Data
Synthetic datasets modeled on real-world patient records for anamnesis workflows.
🔗 Check out the model
Recurv Medical Llama deployed on HuggingFace, click the link below to check more detail.
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