SubhaL/smollm2-disease-symptoms

SmolLM2 Disease Symptoms Model

This is a fine-tuned 360M-parameter SmolLM2 model specialized in answering symptom-related queries for common diseases.

Model Details

• Fine-tuned on symptom-disease Q&A data (~10k examples)
• Training steps: 60
• Use case: symptom listing and healthcare assistance
• Limitations: May sometimes generate clarifying questions or incomplete answers; not a substitute for professional medical advice.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("SubhaL/smollm2-disease-symptoms")
tokenizer = AutoTokenizer.from_pretrained("SubhaL/smollm2-disease-symptoms")

prompt = "What are the symptoms of pneumonia?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))