Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+import joblib
+import numpy as np
+from huggingface_hub import hf_hub_download
+
+model_path = hf_hub_download(
+    repo_id="USERNAME/iris-sklearn-model",
+    filename="model.joblib"
+)
+
+model = joblib.load(model_path)
+
+def predict(sl, sw, pl, pw):
+    x = np.array([[sl, sw, pl, pw]])
+    pred = model.predict(x)[0]
+    return ["setosa", "versicolor", "virginica"][pred]
+
+gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Number(label="Sepal Length"),
+        gr.Number(label="Sepal Width"),
+        gr.Number(label="Petal Length"),
+        gr.Number(label="Petal Width"),
+    ],
+    outputs="text",
+    title="Iris Classification (sklearn)"
+).launch()