out of scope .. again

interfaces/emotion9.py

@@ -58,9 +58,12 @@ def predict(text, model_id, tokenizer_id):
     probs = torch.nn.functional.softmax(logits, dim=1).cpu().numpy().flatten()
 
     if "v2" in model_id:
-        EMOTION9_LABEL_NAMES = EMOTION9_V2_LABEL_NAMES
-    NUMS_DICT = {i: key for i, key in enumerate(sorted(EMOTION9_LABEL_NAMES.keys()))}
-    output_pred = {f"[{NUMS_DICT[i]}] {EMOTION9_LABEL_NAMES[NUMS_DICT[i]]}": probs[i] for i in np.argsort(probs)[::-1]}
+        label_names = EMOTION9_V2_LABEL_NAMES
+    else:
+        label_names = EMOTION9_LABEL_NAMES
+        
+    NUMS_DICT = {i: key for i, key in enumerate(sorted(label_names.keys()))}
+    output_pred = {f"[{NUMS_DICT[i]}] {label_names[NUMS_DICT[i]]}": probs[i] for i in np.argsort(probs)[::-1]}
     output_info = f'<p style="text-align: center; display: block">Prediction was made using the <a href="https://huggingface.co/{model_id}">{model_id}</a> model.</p>'
     return output_pred, output_info