Cognitapp-Med-Nano-v1
Cognitapp-Med-Nano-v1 is a specialized, lightweight medical large language model (LLM) developed by Cognitapp Labs. It is fine-tuned from the Qwen2.5-0.5B architecture to excel at ICD-10-CM Medical Billing and Clinical Extraction.
Key Features
- Global & Regional Awareness: Optimized for both international clinical standards.
- Efficiency: 0.5B parameters, designed for 100% offline use on mobile and desktop devices via MLX or llama.cpp.
- Precision: Trained using prompt-masking to prioritize alphanumeric code accuracy over conversational filler.
How to use with MLX
from mlx_lm import load, generate
model, tokenizer = load("Cognitapp/Cognitapp-Med-Nano-v1")
prompt = "<system>You are the Cognitapp Global ICD-10 Assistant. Extract the primary ICD-10 code.</system> <user>Patient has 103F fever, body aches, and positive NS1 for Dengue.</user> <assistant>"
response = generate(model, tokenizer, prompt=prompt, max_tokens=10)
print(response)
Intended Use
This model is a supportive tool for medical professionals and billers. It is NOT a diagnostic tool.
Training Data
Fine-tuned on a balanced dataset of 1,200+ global and regional clinical scenarios including pediatrics, geriatrics, and infectious diseases.
Disclaimer
All outputs must be verified by a licensed healthcare professional. Cognitapp Labs is not responsible for any clinical or billing errors.
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Model size
0.5B params
Tensor type
BF16
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Hardware compatibility
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