Update app.py

app.py

@@ -12,11 +12,11 @@ inv_label_map = {0: 'B-LOC', 1: 'O', 2: 'B-PERS', 3: 'I-PERS', 4: 'B-ORG', 5: 'I
 
 
 def predict_sent(sentences):
-    input_ids = TOKENIZERr.encode(sentences, return_tensors='pt')
+    input_ids = TOKENIZER.encode(sentences, return_tensors='pt')
 
     with torch.no_grad():
         test_model.to('cpu')
-        output = test_modell(input_ids)
+        output = test_model(input_ids)
     label_indices = np.argmax(output[0].to('cpu').numpy(), axis=2)
 
     tokens = TOKENIZER.convert_ids_to_tokens(input_ids.to('cpu').numpy()[0])