diff --git a/app.py b/app.py
index 608f63a..8544bff 100644
--- a/app.py
+++ b/app.py
@@ -116,8 +116,10 @@ def _extract_images(self, video):
 
     def _classify(self, extracted: list, positions: list, total_ms: int):
         t = time.perf_counter()
-        self.logger.info(f"Initiating classifier with {self.configs['modelName']}")
-        classifier = classify.Classifier(default_model_storage / self.configs['modelName'],
+        model_checkpoint_name = next(default_model_storage.glob(
+            f"*.{self.configs['modelName']}.pos{'T' if self.configs['usePosModel'] else 'F'}.pt"))
+        self.logger.info(f"Initiating classifier with {model_checkpoint_name.stem}")
+        classifier = classify.Classifier(model_checkpoint_name, 
                                          self.logger.name if self.logger.isEnabledFor(logging.DEBUG) else None)
         if self.logger.isEnabledFor(logging.DEBUG):
             self.logger.debug(f"Classifier initiation took {time.perf_counter() - t:.2f} seconds")
diff --git a/metadata.py b/metadata.py
index 43c808a..303aa46 100644
--- a/metadata.py
+++ b/metadata.py
@@ -70,8 +70,11 @@ def appmetadata() -> AppMetadata:
     metadata.add_parameter(
         name='modelName', type='string', 
         default='convnext_lg',
-        choices=[m.stem[16:] for m in available_models],
+        choices=[m.stem.split('.')[1] for m in available_models],
         description='model name to use for classification')
+    metadata.add_parameter(
+        name='usePosModel', type='boolean', default=True,
+        description='Use the model trained with positional features')
     metadata.add_parameter(
         name='useStitcher', type='boolean', default=True,
         description='Use the stitcher after classifying the TimePoints')