diff --git a/.vscode/launch.json b/.vscode/launch.json
index 5a826496cc1f..7cb46d0c698d 100644
--- a/.vscode/launch.json
+++ b/.vscode/launch.json
@@ -11,6 +11,7 @@
             "env": {
                 "LOG_LEVEL": "DEBUG",
                 "PYTHONPATH": "${workspaceFolder}:${PYTHONPATH}",
+                "SLY_APP_DATA_DIR": "${workspaceFolder}/results",
             }
         },
         {
@@ -35,13 +36,8 @@
                 "PYTHONPATH": "${workspaceFolder}:${PYTHONPATH}",
                 "LOG_LEVEL": "DEBUG",
                 "ENV": "production",
-                "TEAM_ID": "277",
-                "WORKSPACE_ID": "403",
                 "DEBUG_WITH_SLY_NET": "1",
                 "SLY_APP_DATA_DIR": "${workspaceFolder}/results",
-                "modal.state.modelWeightsOptions": "pretrained",
-                "modal.state.selectedModel": "YOLOv5s",
-                "modal.state.weightsPath": ""
             }
         }
     ]
diff --git a/requirements.txt b/requirements.txt
index 489a8b43bb5f..94d179bfd9d3 100755
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,5 @@
 # pip install -r requirements.txt
-supervisely==6.69.15
+supervisely==6.69.70
 
 opencv-python-headless==4.5.5.62
 opencv-python==4.5.5.62
diff --git a/supervisely/serve/local.env b/supervisely/serve/local.env
index 7e2d09608b87..67c36abf293d 100644
--- a/supervisely/serve/local.env
+++ b/supervisely/serve/local.env
@@ -1,13 +1,11 @@
 PYTHONUNBUFFERED=1
 
 APP_NAME="Serve YOLOv5"
-SLY_APP_DATA_DIR="./data_dir"
-LOG_LEVEL="trace"
 
-context.teamId=277
-context.workspaceId=403
+TEAM_ID=440
+WORKSPACE_ID=662
 
+# "pretrained" or "custom"
 modal.state.modelWeightsOptions="pretrained"
-#"pretrained" "custom"
 modal.state.selectedModel="YOLOv5s"
 modal.state.weightsPath=""
diff --git a/supervisely/serve/src/main.py b/supervisely/serve/src/main.py
index 09916f4051ac..09caa686d60a 100644
--- a/supervisely/serve/src/main.py
+++ b/supervisely/serve/src/main.py
@@ -26,17 +26,21 @@
 pretrained_weights = os.environ['modal.state.selectedModel'].lower()
 custom_weights = os.environ['modal.state.weightsPath']
 
+pretrained_weights_url = f"https://github.com/ultralytics/yolov5/releases/download/v5.0/{pretrained_weights}.pt"
+
 class YOLOv5Model(sly.nn.inference.ObjectDetection):
     def load_on_device(
         self,
+        model_dir: str = None,
         device: Literal["cpu", "cuda", "cuda:0", "cuda:1", "cuda:2", "cuda:3"] = "cpu",
     ):
         # download weights
         if model_weights_options == "pretrained":
-            self.local_weights_path = self.location
+            self.local_weights_path = self.download(pretrained_weights_url)
         if model_weights_options == "custom":
-            self.local_weights_path = self.location[0]
-            configs_local_path = self.location[1]
+            self.local_weights_path = self.download(custom_weights)
+            cfg_path_in_teamfiles = os.path.join(Path(custom_weights).parents[1], 'opt.yaml')
+            configs_local_path = self.download(cfg_path_in_teamfiles)
 
         self.device = select_device(device)
         self.half = self.device.type != 'cpu'  # half precision only supported on CUDA
@@ -138,7 +142,6 @@ def predict(
 
         return predictions
 
-
     def predict_raw(
         self, image_path: str, settings: Dict[str, Any]
     ) -> List[sly.nn.PredictionBBox]:
@@ -188,20 +191,11 @@ def predict_raw(
 device = "cuda" if torch.cuda.is_available() else "cpu"
 print("Using device:", device)
 
-if model_weights_options == "pretrained":
-    location = f"https://github.com/ultralytics/yolov5/releases/download/v5.0/{pretrained_weights}.pt"
-elif model_weights_options == "custom":
-    location = [
-        custom_weights, # model weights
-        os.path.join(Path(custom_weights).parents[1], 'opt.yaml') # model config
-    ]
-
 m = YOLOv5Model(
-    location=location, 
     custom_inference_settings=os.path.join(app_source_path, "custom_settings.yaml"),
     sliding_window_mode = "advanced"
 )
-m.load_on_device(device)
+m.load_on_device(device=device)
 
 if sly.is_production():
     # this code block is running on Supervisely platform in production