Update app.py

app.py

@@ -23,6 +23,8 @@ def md_loading():
     ## cpu
     # device = torch.device('cpu')
 
+    device = torch.device("cpu")
+
     tokenizer = XLMRobertaTokenizer.from_pretrained('xlm-roberta-large')
     model = XLMRobertaForSequenceClassification.from_pretrained('xlm-roberta-large', num_labels=493)
     
@@ -30,14 +32,15 @@ def md_loading():
     project_path = './'
     output_model_file = os.path.join(project_path, model_checkpoint)
 
-    model.load_state_dict(torch.load(output_model_file, map_location=torch.device('cpu')))
+    model.load_state_dict(torch.load(output_model_file)
+#    model.load_state_dict(torch.load(output_model_file, map_location=torch.device('cpu')))
 #    ckpt = torch.load(output_model_file, map_location=torch.device('cpu'))
 #    model.load_state_dict(ckpt['model_state_dict'])
     
 #    device = torch.device("cuda" if torch.cuda.is_available() and not False else "cpu")
 #    device = torch.device("cpu")
         
-#    model.to(device)
+    model.to(device)
     
     label_tbl = np.load('./label_table.npy')
     loc_tbl = pd.read_csv('./kisc_table.csv', encoding='utf-8')