--- a
+++ b/examples/local.py
@@ -0,0 +1,41 @@
+#!/usr/bin/env python
+
+__doc__ = """
+Simple example script showing how to use the Sybil library locally to predict risk scores for a set of DICOM files.
+"""
+
+import sybil
+from sybil import visualize_attentions
+
+from utils import get_demo_data
+
+
+def main():
+    # Load a trained model
+    model = sybil.Sybil("sybil_ensemble")
+
+    dicom_files = get_demo_data()
+
+    # Get risk scores
+    serie = sybil.Serie(dicom_files)
+    print(f"Processing {len(dicom_files)} DICOM files")
+    prediction = model.predict([serie], return_attentions=True)
+    scores = prediction.scores
+
+    print(f"Risk scores: {scores}")
+
+    # Visualize attention maps
+    output_dir = "sybil_attention_output"
+
+    print(f"Writing attention images to {output_dir}")
+    series_with_attention = visualize_attentions(
+        serie,
+        attentions=prediction.attentions,
+        save_directory=output_dir,
+        gain=3,
+    )
+
+    print(f"Finished writing attention images to {output_dir}")
+
+if __name__ == "__main__":
+    main()