testing

app.py

@@ -43,12 +43,13 @@ result = model(encoding)
 
 # transform logit to get probabilities
 prediction = nn.functional.softmax(result.logits, dim=-1)
-neutralProb = prediction.data[0][neutralIndex]
-toxicProb = prediction.data[0][toxicIndex]
+prediction
+#neutralProb = prediction.data[0][neutralIndex]
+#toxicProb = prediction.data[0][toxicIndex]
 
 # Expected returns from RoBERTa on default text:
 # Neutral: 0.0052
 # Toxic: 0.9948
 st.write("Classification Probabilities")
-st.write(f"{neutralProb:.4f} - NEUTRAL")
-st.write(f"{toxicProb:.4f} - TOXIC")
+#st.write(f"{neutralProb:.4f} - NEUTRAL")
+#st.write(f"{toxicProb:.4f} - TOXIC")