test

app.py

@@ -113,11 +113,11 @@ if option == 'MILESTONE 3':
     df = df.assign(Highest_Toxicity_Class_Except_Toxic=HTCET)
     df = df.assign(Score_Except_Toxic=SET)
 
-    X_train = pre_populated_tweets[0]
+    X_train = 'I dont anonymously edit articles at all.'
     batch = tokenizers[0](X_train, padding=True, truncation=True, max_length=512, return_tensors="pt")
 
     with torch.no_grad():
-        outputs = models[0](**batch, labels=torch.tensor([1, 0]))
+        outputs = models[0](batch, labels=torch.tensor([1, 0]))
         predictions = F.softmax(outputs.logits, dim=1)
         labels = torch.argmax(predictions, dim=1)
         labels = [model.config.id2label[label_id] for label_id in labels.tolist()]