Update interfaces/emotion9.py

interfaces/emotion9.py

@@ -37,6 +37,8 @@ def predict(text, model_id, tokenizer_id):
     with torch.no_grad():
         logits = model(**inputs).logits
 
+    probs = torch.nn.functional.softmax(logits, dim=1).cpu().numpy().flatten()
+
     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]}
     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>'