Update app.py

app.py

@@ -12,6 +12,7 @@ tokenizer=BertTokenizer.from_pretrained("./")
 
 
 def predict(text=None) -> dict:  
+    print(text)
     model.eval()
     inputs = tokenizer(text, return_tensors="pt")
     input_ids = inputs["input_ids"].to(device)
@@ -23,7 +24,8 @@ def predict(text=None) -> dict:
     top_5_tokens = torch.topk(mask_token_logits, NUM_CLASSES, dim=1).indices[0].tolist()
     score = torch.nn.functional.softmax(mask_token_logits)[0]
     top_5_score = torch.topk(score, NUM_CLASSES).values.tolist()
-    return {tokenizer.decode([tok]): score for tok, score in zip(top_5_tokens, top_5_score)}
+    print(top_5_tokens)
+    return {tokenizer.decode([tok]): float(score) for tok, score in zip(top_5_tokens, top_5_score)}
     
 gr.Interface(fn=predict, 
              inputs=gr.inputs.Textbox(lines=2, placeholder="Your Text… "),