interpretation info

interfaces/cap_minor_media.py

@@ -126,7 +126,20 @@ def predict(text, major_model_id, minor_model_id, tokenizer_id, HF_TOKEN=None):
 
     output_info = f'<p style="text-align: center; display: block">Prediction used <a href="https://huggingface.co/{major_model_id}">{major_model_id}</a> and <a href="https://huggingface.co/{minor_model_id}">{minor_model_id}</a>.</p>'
 
-    return output_pred, output_info
+    interpretation_info = """
+    ## How to Interpret These Values (Hierarchical Classification)
+
+    This method returns either:
+
+    - A list of **major (media) topic confidences**, or
+    - A list of **minor topic confidences**.
+
+    In the case of minor topics, the values are the confidences for minor topics **within a given major topic**, and they are **normalized to sum to 1**.
+
+    **Note:** This method cannot return a mix of major and minor topic predictions.
+    """
+
+    return interpretation_info, output_pred, output_info
 
 def predict_cap(tmp, method, text, language, domain):
     domain = domains[domain]
@@ -161,4 +174,4 @@ demo = gr.Interface(
             gr.Textbox(lines=6, label="Input"),
             gr.Dropdown(languages, label="Language"),
             gr.Dropdown(domains.keys(), label="Domain")],
-    outputs=[gr.Label(label="Output"), gr.Markdown()])
+    outputs=[gr.Markdown(), gr.Label(label="Output"), gr.Markdown()])