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---
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) |