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Slyracoon23/medical-gemma3n-emergency-response
medical-gemma3n-emergency-response is a text generation model from Slyracoon23. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
A fine-tuned version of Gemma 3N designed for emergency response scenarios. Powers the Citizen2Responder app with dual-mode capabilities: natural guidance for bystanders and structured tool outputs for EMTs — all with…
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From the Hugging Face model README
A fine-tuned version of Gemma 3N designed for emergency response scenarios. Powers the Citizen2Responder app with dual-mode capabilities: natural guidance for bystanders and structured tool outputs for EMTs — all with a privacy-first, local deployment focus.
unsloth/gemma-3n-E4B-itfrom transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Slyracoon23/medical-gemma3n-emergency-response")
tokenizer = AutoTokenizer.from_pretrained("Slyracoon23/medical-gemma3n-emergency-response")
# Natural guidance mode
prompt = "Someone collapsed and is not responding. What should I assess first?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
llama.rn@misc{medical-gemma3n-emergency-response,
title={Medical Emergency Response AI - Gemma 3N Fine-tuned},
author={Citizen2Responder Team},
year={2025},
url={https://huggingface.co/Slyracoon23/medical-gemma3n-emergency-response},
note={Fine-tuned for dual-mode emergency response with privacy-first architecture}
}
This model is for educational and emergency guidance only. Always contact professional medical services in real emergencies.