add padding to xlm

app.py

@@ -26,8 +26,8 @@ elif (option == "DistilBERT"):
 elif (option == "XLM-RoBERTa"):
     tokenizerPath = "unitary/multilingual-toxic-xlm-roberta"
     modelPath = "unitary/multilingual-toxic-xlm-roberta"
-    neutralIndex = 0
-    toxicIndex = 1
+    neutralIndex = 1
+    toxicIndex = 0
 else:
     tokenizerPath = "s-nlp/roberta_toxicity_classifier"
     modelPath = "s-nlp/roberta_toxicity_classifier"
@@ -42,6 +42,9 @@ model = AutoModelForSequenceClassification.from_pretrained(modelPath)
 encoding = tokenizer.encode(txt, return_tensors='pt')
 result = model(encoding)
 result
+pad = (0, 1)
+nn.functional.pad(result.logits, pad, "constant", 0)
+result
 
 # transform logit to get probabilities
 prediction = nn.functional.softmax(result.logits, dim=-1)