🧠 Qwen3-1.7B-MedicalDataset

A fine-tuned version of Qwen3-1.7B on a curated medical dataset, designed to assist with medical Q&A, clinical documentation, and healthcare-related reasoning. Developed by XformAI-India.

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📌 Model Details

• Base Model: Qwen3-1.7B (from Qwen by Alibaba)
• Architecture: Transformer Decoder (GPT-like)
• Parameters: 1.7 Billion
• Precision: bfloat16 / float16
• Fine-tuning method: Supervised fine-tuning (SFT)
• Dataset: FreedomIntelligence/medical-o1-reasoning-SFT

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🧪 Intended Use

This model is intended for research and educational purposes in the following domains:

• Medical question answering
• Summarizing patient records
• Medical reasoning and triage
• Chatbot integration for healthcare support (non-diagnostic)

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🚫 Limitations & Disclaimer

⚠️ Not for clinical use. This model is not a replacement for professional medical advice, diagnosis, or treatment.

• May hallucinate or produce incorrect medical information.
• Trained only on publicly available or synthetic datasets — not real patient data.
• Should not be used in emergency or high-stakes settings.

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💡 Example Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("XformAI-india/Qwen3-1.7B-medicaldataset", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("XformAI-india/Qwen3-1.7B-medicaldataset", trust_remote_code=True)

prompt = "Patient presents with chest pain and shortness of breath. What are possible differential diagnoses?"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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🏗 Training Configuration

• Epochs: 3
• Batch Size: 8
• Optimizer: AdamW
• Learning Rate: 2e-5
• Gradient Accumulation: 4
• Framework: PyTorch, Hugging Face Transformers

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🧠 Citation

If you use this model, please cite:

@misc{qwen3medical2025,
  title={Qwen3-1.7B-MedicalDataset: A Fine-Tuned Transformer for Medical AI Research},
  author={XformAI-India},
  year={2025},
  url={https://huggingface.co/XformAI-india/Qwen3-1.7B-medicaldataset}
}

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