Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,69 @@
+---
+tags:
+  - text-classification
+  - medical
+  - prototypical-networks
+  - transformers
+library_name: transformers
+language: en
+license: mit
+datasets:
+  - your_dataset_name_here
+model-index:
+  - name: ProtoPatient
+    results:
+      - task:
+          type: multi-label-classification
+        dataset:
+          name: your_dataset_name_here
+          type: text
+        metrics:
+          - name: Accuracy
+            type: accuracy
+            value: 0.XX  # Update with real value
+          - name: F1-score
+            type: f1
+            value: 0.XX  # Update with real value
+---
+
+
+
+# ProtoPatient Model for Multi-Label Classification
+
+This repository contains the implementation of the ProtoPatient model, designed for multi-label classification tasks. It is based on a transformer model and integrates a prototype-based learning approach.
+
+ProtoPatient is a novel method using prototypical networks and label-wise attention for diagnosis prediction from clinical text, ensuring both accuracy and interpretability by making predictions based on text segments similar to prototypical patients. Evaluated on two clinical datasets, it outperforms existing baselines and provides explanations that are understandable and valuable for doctors.
+
+## **Repository Structure**
+```
+ProtoPatient/
+│── proto_model/
+│   ├── proto.py
+│   ├── utils.py
+│   ├── metrics.py
+│   ├── __init__.py
+│── config.json
+│── model.safetensors
+│── tokenizer.json
+│── tokenizer_config.json
+│── vocab.txt
+│── README.md
+│── .gitattributes
+```
+
+## **How to Use the Model**
+
+### **1. Install Dependencies**
+Ensure you have `transformers` and `torch` installed:
+```bash
+pip install transformers torch
+```
+
+### **2. Load the Model**
+You can load the model as follows:
+```python
+from transformers import AutoModel
+
+model = AutoModel.from_pretrained("row56/ProtoPatient")
+print("✅ Model with weights loaded successfully!")
+```