testmodel

app.py

@@ -58,15 +58,15 @@ if option == 'MILESTONE 3':
     # classifiers = [classifier_0, classifier_1, classifier_2, classifier_3, classifier_4, classifier_5]
 
     X_train = [textIn]
-    batch = tokenizer(X_train, padding=True, truncation=True, max_length=512, return_tensors="pt")
+    batch_0 = tokenizer_0(X_train, padding=True, truncation=True, max_length=512, return_tensors="pt")
 
     with torch.no_grad():
-        outputs = model(**batch, labels=torch.tensor([1, 0]))
+        outputs = model(**batch_0, 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()]
 
-    st.write(outputs['label'])
+    st.write(predictions['label'])
 
 
     col = ['Tweet', 'Highest_Toxicity_Class_Overall', 'Score_Overall', 'Highest_Toxicity_Class_Except_Toxic', 'Score_Except_Toxic']