Update app.py

app.py

@@ -10,14 +10,15 @@ st.title('GPT2:')
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 @st.cache(allow_output_mutation=True)
 def get_model():
-    tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln")
-    model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln6")
+    #model = #AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln6")
     #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln5")
     #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln4")
     #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln3")
     #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln2")
     #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln")
     #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln24")
+    tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln")
+    model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln25")
     model.to(device)
     return model, tokenizer