Upload 2 files

app.py

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+
+import gradio as gr
+from huggingface_hub import hf_hub_download
+import joblib
+import numpy as np
+
+# Load model from Hub
+model_repo = "leorigasaki54/earthquake-magnitude-predictor"
+model = joblib.load(hf_hub_download(repo_id=model_repo, filename="rf_earthquake_mag.joblib"))
+
+def predict(feature1, feature2, feature3, feature4, feature5):
+    input_data = np.array([[feature1, feature2, feature3, feature4, feature5]])
+    return model.predict(input_data)[0]
+
+# Adjust labels/features based on your model's input requirements
+inputs = [
+    gr.Number(label="Feature 1 (e.g., Seismic Signal)"),
+    gr.Number(label="Feature 2 (e.g., Depth)"),
+    gr.Number(label="Feature 3 (e.g., Latitude)"),
+    gr.Number(label="Feature 4 (e.g., Longitude)"),
+    gr.Number(label="Feature 5 (e.g., Station Distance)")
+]
+
+gr.Interface(
+    fn=predict,
+    inputs=inputs,
+    outputs=gr.Number(label="Predicted Magnitude"),
+    title="Earthquake Magnitude Predictor",
+    description="Predict earthquake magnitude using seismic data"
+).launch()

requirements.txt

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+gradio>=4.0
+scikit-learn>=1.0
+joblib
+huggingface-hub
+numpy