large model config fix

model.py

@@ -18,7 +18,7 @@ config = dict(
     
     # model info
     tokenizer_path = 'roberta-large', # 'allenai/biomed_roberta_base',
-    model_checkpoint = 'model_large_pseudo_label.pth', # 'allenai/biomed_roberta_base', 
+    model_checkpoint = 'roberta-large', # 'allenai/biomed_roberta_base', 
     device = 'cuda' if torch.cuda.is_available() else 'cpu',
     
     # training paramters
@@ -334,7 +334,7 @@ def get_predictions(feature_text, pn_history):
     return pred_string
 
 tokenizer = AutoTokenizer.from_pretrained(config['tokenizer_path'])
-path = 'model.pth'
+path = 'model_large_pseudo_label.pth'
 
 model = NBMEModel().to(config['device'])
 model.load_state_dict(