---
language: en
library_name: transformers
pipeline_tag: image-classification
tags:
- vision
- cervical-cancer
- diagnosis
license: apache-2.0
---

# 🩺 MedSigLip Diagnosis Model

This repository contains **MedSigLip**, a deep learning model for cervical cancer image diagnosis.  
It takes colposcopy images as input and predicts the most likely stage/class of the condition.  

---

## 📊 Model Details
- **Task:** Image Classification  
- **Domain:** Healthcare – Cervical Cancer Diagnosis  
- **Framework:** Hugging Face Transformers / PyTorch  
- **Author:** Khanyi Tapiwa Magagula (AI Eswatini)  

---

## 🚀 Inference API

Once the **Inference API** is enabled, you can run predictions without any setup. Example:

```python
from huggingface_hub import InferenceClient

# Replace with your repo name
client = InferenceClient("KhanyiTapiwa00/medsiglip-diagnosis")

# Run image classification
result = client.image_classification("1_10.jpg")

print(result)