Update app.py

app.py

@@ -109,7 +109,6 @@ def predict_icd(text_input, model_name, label_count):
             "args": training_args
         }
         model = model_class.from_pretrained(model_path, **kwargs)
-        model.to(torch.device("cuda:0"))
         tokenizer = AutoTokenizer.from_pretrained(model_args.tokenizer_name,  padding_side="right")
         results = segment_tokenize_dataset(tokenizer, text, labels,
                                            data_args.max_seq_length,
@@ -124,10 +123,10 @@ def predict_icd(text_input, model_name, label_count):
 
 
         with torch.no_grad():
-            input_ids = input_ids.to(torch.device("cuda:0"))
-            attention_mask = attention_mask.to(torch.device("cuda:0"))
-            token_type_ids = token_type_ids.to(torch.device("cuda:0"))
-            targets = targets.to(torch.device("cuda:0"))
+            # input_ids = input_ids.to(torch.device("cuda:0"))
+            # attention_mask = attention_mask.to(torch.device("cuda:0"))
+            # token_type_ids = token_type_ids.to(torch.device("cuda:0"))
+            # targets = targets.to(torch.device("cuda:0"))
             model_inputs = {
                             "input_ids": input_ids,
                             "attention_mask": attention_mask,