---
title: Iris Flower Classifier
emoji: 🌸
colorFrom: purple
colorTo: pink
sdk: gradio
app_file: app.py
pinned: false
license: mit
---

# Iris Flower Classifier

A Random Forest model (scikit-learn) that predicts the species of an iris flower
(setosa, versicolor, virginica) from four measurements in centimetres:
sepal length, sepal width, petal length and petal width.

- **Training data:** the classic Iris dataset (150 samples, 3 classes)
- **Algorithm:** RandomForestClassifier, 100 trees
- **Test accuracy:** 90% on a 20% hold-out split

## Use it in Python

```python
import joblib
from huggingface_hub import hf_hub_download

bundle = joblib.load(hf_hub_download("your-username/iris-classifier", "model.joblib"))
model, classes = bundle["model"], bundle["classes"]
print(classes[model.predict([[5.1, 3.5, 1.4, 0.2]])[0]])  # setosa
```