SilverCareAI-14B: Expert Model for Structured Health Data and Medical Q&A

SilverCareAI-14B is a 14.2 billion parameter language model, fine-tuned from the powerful Qwen/Qwen1.5-14B base. It is specifically designed for two primary functions in the healthcare domain: generating structured health reports and providing medical question-answering.

Key Capabilities

• High-Fidelity Structured Output: Reliably produces valid JSON objects following predefined schemas, even from incomplete input data.
• Complex Instruction Following: Fine-tuned with a detailed system prompt to execute intricate algorithmic logic for diagnoses and health scoring.
• Robust Missing Data Handling: Gracefully processes incomplete inputs by skipping analysis for missing fields, preventing hallucination.
• Bilingual Proficiency: Inherits strong Chinese and English capabilities from its Qwen1.5-14B base.
• Medical Q&A: Functions as a knowledgeable medical assistant for general health inquiries, trained on a comprehensive dataset.

Training Details

The model was fine-tuned using the LLaMA Factory framework with QLoRA on a custom dataset. This dataset comprised high-quality structured health records paired with JSON reports to teach algorithmic reasoning, alongside a broad set of general medical Q&A pairs to enhance conversational knowledge.

Important Considerations

SilverCareAI-14B is not a medical professional or diagnostic tool. Its outputs are for informational and reference purposes only and should not replace consultation with qualified healthcare providers. Users must include clear disclaimers in any application utilizing this model. Limitations include potential factual inaccuracies, a knowledge cutoff based on its training data, and possible biases reflecting the training data.