smolify/smolified-clinical-symptom-router
The smolify/smolified-clinical-symptom-router is a 0.3 billion parameter Domain Specific Language Model (DSLM) developed by Smolify Foundry. This micro-architecture model is synthetically distilled from state-of-the-art reasoning engines, optimized for high-efficiency deployment on edge hardware or low-VRAM environments. It is specifically designed for clinical triage, identifying appropriate hospital departments and assigning urgency levels based on patient symptom descriptions.
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smolified-clinical-symptom-router: A Specialized Clinical Triage Model
This model, developed by the Smolify Foundry, is a Domain Specific Language Model (DSLM) specifically engineered for clinical symptom routing. It represents a new class of highly efficient, specialized AI.
Key Capabilities & Features
- Domain Specific: Optimized for clinical triage tasks, identifying hospital departments and urgency levels from symptom descriptions.
- High Efficiency: Synthetically distilled from larger reasoning engines into a micro-architecture (270M parameter class), making it suitable for deployment on edge hardware (CPU/NPU) or environments with limited VRAM.
- Optimized Deployment: Available in 4-bit Quantized / FP16 Mixed formats for maximum performance and minimal resource usage.
- Proprietary Neural Distillation: Utilizes advanced, proprietary methods for its training and optimization.
Ideal Use Cases
- Clinical Triage: Automatically routing patient symptom descriptions to the correct hospital department (e.g., Emergency, Urgent, Routine).
- Edge Deployment: Applications requiring on-device AI for medical pre-screening or initial assessment where computational resources are constrained.
- Low-VRAM Environments: Integrating AI-powered clinical assistance into systems with limited GPU memory.
This model is a sovereign asset owned by smolify, generated via Smolify.ai, and is compatible with standard inference backends like vLLM.