Update app.py

app.py

@@ -18,8 +18,9 @@ def predict(text=None) -> dict:
     attention_mask = inputs["attention_mask"].to(device)
     model.to(device)
     token_logits = model(input_ids, attention_mask=attention_mask).logits
-    print(mask_token_index)
+    print(token_logits )
     mask_token_index = torch.where(inputs["input_ids"] == tokenizer.mask_token_id)[1]
+    print(mask_token_index)
     mask_token_logits = token_logits[0, mask_token_index, :]
     print(mask_token_logits)
     top_5_tokens = torch.topk(mask_token_logits, NUM_CLASSES, dim=1).indices[0].tolist()