cpu version

utils.py

@@ -200,7 +200,7 @@ class MolecularPropertyPredictionModel():
             self.base_model.load_adapter(adapter_id, adapter_name=adapter_name, token = os.environ.get("TOKEN"))
             self.apapter_scaler_path[adapter_name] = hf_hub_download(adapter_id, filename="scaler.pkl", token = os.environ.get("TOKEN"))
 
-        self.base_model.to("cuda")
+        #self.base_model.to("cuda")
         print(self.base_model)
     
     def swith_adapter(self, adapter_name, adapter_id):
@@ -241,7 +241,7 @@ class MolecularPropertyPredictionModel():
         # construct the dataloader
         test_loader = torch.utils.data.DataLoader(
             test_dataset,
-            batch_size=32,
+            batch_size=16,
             collate_fn=self.data_collator,
         )
         # predict