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unsloth/gemma-3n-E4B-it1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained("Slyracoon23/medical-gemma3n-emergency-response")
4tokenizer = AutoTokenizer.from_pretrained("Slyracoon23/medical-gemma3n-emergency-response")
5
6# Natural guidance mode
7prompt = "Someone collapsed and is not responding. What should I assess first?"
8inputs = tokenizer(prompt, return_tensors="pt")
9outputs = model.generate(**inputs, max_length=200, temperature=0.7)
10print(tokenizer.decode(outputs[0], skip_special_tokens=True))llama.rn1@misc{medical-gemma3n-emergency-response,
2 title={Medical Emergency Response AI - Gemma 3N Fine-tuned},
3 author={Citizen2Responder Team},
4 year={2025},
5 url={https://huggingface.co/Slyracoon23/medical-gemma3n-emergency-response},
6 note={Fine-tuned for dual-mode emergency response with privacy-first architecture}
7}