Update app.py

app.py

@@ -30,7 +30,7 @@ def predict(outputs):
     top = 0
     temp = 30000
     apr_probs = torch.nn.functional.softmax(torch.tensor([39253., 84., 220., 2263., 1214., 909., 66., 10661.]) / temp, dim=0)
-    probs = nn.functional.softmax(outputs * apr_probs, dim=1).tolist()[0]
+    probs = nn.functional.softmax(outputs / apr_probs, dim=1).tolist()[0]
     
     top_cats = []
     top_probs = []
@@ -57,7 +57,7 @@ tokenizer = RobertaTokenizer.from_pretrained("roberta-large-mnli")
 model = init_model()
 
 st.title("Article classifier")
-st.markdown("<img width=500px src='https://lionbridge.ai/wp-content/uploads/2020/09/2020-09-08_text-classification-tools-services.jpg'>", unsafe_allow_html=True)
+st.markdown("<img width=500px src='https://lionbridge.ai/wp-content/uploads/2020/09/2020-09-08_text-classification-tools-services.jpg', class='center'>", unsafe_allow_html=True)
 st.markdown("### Title")
 
 title = st.text_area("*Enter title (required)", height=20)