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README.md

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+---
+license: apache-2.0
+tags:
+  - medical
+  - clinical-notes
+  - patient-communication
+  - lora
+  - peft
+  - medgemma
+language:
+  - en
+library_name: peft
+---
+
+# NoteExplain Models
+
+Trained models for clinical note simplification - translating medical documents into patient-friendly language.
+
+## Models
+
+| Model | Base | Description | Overall | Accuracy | Patient-Centered |
+|-------|------|-------------|---------|----------|------------------|
+| **gemma-2b-distilled** | gemma-2-2b-it | Final mobile model | 70% | 73% | **76%** |
+| **gemma-2b-dpo** | gemma-2-2b-it | DPO comparison | **73%** | **82%** | 61% |
+| **gemma-9b-dpo** | gemma-2-9b-it | Teacher model | 79% | 91% | 70% |
+
+## Usage
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the distilled model (recommended for deployment)
+base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it")
+tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-2b-it")
+model = PeftModel.from_pretrained(base_model, "dejori/note-explain", subfolder="gemma-2b-distilled")
+
+# Or load the DPO model (higher accuracy)
+model = PeftModel.from_pretrained(base_model, "dejori/note-explain", subfolder="gemma-2b-dpo")
+
+# Generate
+prompt = "Simplify this clinical note for a patient:\n\n[clinical note]\n\nSimplified version:"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Training
+
+- **DPO Training**: MedGemma-27B scored 5 candidate outputs per clinical note, creating preference pairs
+- **Distillation**: 9B-DPO model generated high-quality outputs to train the 2B model via SFT
+
+## Dataset
+
+Training data: [dejori/note-explain-clinical](https://huggingface.co/datasets/dejori/note-explain-clinical)
+
+## Citation
+
+```bibtex
+@misc{noteexplain2026,
+  title={NoteExplain: Privacy-First Clinical Note Simplification},
+  author={Dejori, Mathaeus},
+  year={2026},
+  publisher={HuggingFace}
+}
+```
+
+## License
+
+Apache 2.0