Update app.py

app.py

@@ -6,10 +6,8 @@ import torch.nn as nn
 from transformers import RobertaTokenizer, RobertaModel
 
 
-@st.cache(hash_funcs={tokenizers.AddedToken: lambda _: None, _regex.Pattern: lambda _: None})
-def init():
-    tokenizer = RobertaTokenizer.from_pretrained("roberta-large-mnli")
-
+@st.cache(suppress_st_warning=True)
+def init_model():
     model = RobertaModel.from_pretrained("roberta-large-mnli")
 
     model.pooler = nn.Sequential(
@@ -23,7 +21,7 @@ def init():
     model_path = 'model.pt'
     model.load_state_dict(torch.load(model_path, map_location=torch.device("cpu")))
     model.eval()
-    return tokenizer, model
+    return model
 
 cats = ['Computer Science', 'Economics', 'Electrical Engineering', 
         'Mathematics', 'Physics', 'Biology', 'Finance', 'Statistics']
@@ -38,7 +36,8 @@ def predict(outputs):
             top += percent
             st.write(f'{cat}: {round(percent, 1)}')
 
-tokenizer, model = init()
+tokenizer = RobertaTokenizer.from_pretrained("roberta-large-mnli")
+model = init_model()
         
 st.markdown("### Title")