Update app.py

app.py

@@ -3,8 +3,30 @@ import torch
 import torch.nn.functional as TF
 import streamlit as st
 
+model_name = "RoBERTa"
+
 classifier = pipeline("sentiment-analysis")
 defaultTxt = "I hate you cancerous insects so much"
 result = classifier(defaultTxt)
-
 st.write(result)
+
+if (option == "RoBERTa"):
+    tokenizerPath = "s-nlp/roberta_toxicity_classifier"
+    modelPath = "s-nlp/roberta_toxicity_classifier"
+    neutralIndex = 0
+    toxicIndex = 1
+elif (option == "DistilBERT"):
+    tokenizerPath = "citizenlab/distilbert-base-multilingual-cased-toxicity"
+    modelPath = "citizenlab/distilbert-base-multilingual-cased-toxicity"
+    neutralIndex = 1
+    toxicIndex = 0
+elif (option == "XLM-RoBERTa"):
+    tokenizerPath = "unitary/multilingual-toxic-xlm-roberta"
+    modelPath = "unitary/multilingual-toxic-xlm-roberta"
+    neutralIndex = 1
+    toxicIndex = 0
+else:
+    tokenizerPath = "s-nlp/roberta_toxicity_classifier"
+    modelPath = "s-nlp/roberta_toxicity_classifier"
+    neutralIndex = 0
+    toxicIndex = 1