diff --git a/examples/count_people_in_zone/inference_example.py b/examples/count_people_in_zone/inference_example.py
index e040a036..38018c16 100644
--- a/examples/count_people_in_zone/inference_example.py
+++ b/examples/count_people_in_zone/inference_example.py
@@ -35,9 +35,7 @@ def load_zones_config(file_path: str) -> List[np.ndarray]:
 
 def initiate_annotators(
     polygons: List[np.ndarray], resolution_wh: Tuple[int, int]
-) -> Tuple[
-    List[sv.PolygonZone], List[sv.PolygonZoneAnnotator], List[sv.BoxAnnotator]
-]:
+) -> Tuple[List[sv.PolygonZone], List[sv.PolygonZoneAnnotator], List[sv.BoxAnnotator]]:
     line_thickness = sv.calculate_optimal_line_thickness(resolution_wh=resolution_wh)
     text_scale = sv.calculate_optimal_text_scale(resolution_wh=resolution_wh)
 
diff --git a/examples/count_people_in_zone/ultralytics_example.py b/examples/count_people_in_zone/ultralytics_example.py
index f8d03fa4..04169597 100644
--- a/examples/count_people_in_zone/ultralytics_example.py
+++ b/examples/count_people_in_zone/ultralytics_example.py
@@ -33,9 +33,7 @@ def load_zones_config(file_path: str) -> List[np.ndarray]:
 
 def initiate_annotators(
     polygons: List[np.ndarray], resolution_wh: Tuple[int, int]
-) -> Tuple[
-    List[sv.PolygonZone], List[sv.PolygonZoneAnnotator], List[sv.BoxAnnotator]
-]:
+) -> Tuple[List[sv.PolygonZone], List[sv.PolygonZoneAnnotator], List[sv.BoxAnnotator]]:
     line_thickness = sv.calculate_optimal_line_thickness(resolution_wh=resolution_wh)
     text_scale = sv.calculate_optimal_text_scale(resolution_wh=resolution_wh)
 
diff --git a/supervision/__init__.py b/supervision/__init__.py
index 556e5d09..2366a83c 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -45,7 +45,6 @@ from supervision.detection.line_zone import (
     LineZoneAnnotator,
     LineZoneAnnotatorMulticlass,
 )
-from supervision.detection.vlm import LMM, VLM
 from supervision.detection.overlap_filter import (
     OverlapFilter,
     box_non_max_merge,
@@ -78,6 +77,7 @@ from supervision.detection.utils import (
     xywh_to_xyxy,
     xyxy_to_polygons,
 )
+from supervision.detection.vlm import LMM, VLM
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import (
     calculate_optimal_line_thickness,
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 49ce45ec..4590ad96 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -36,7 +36,6 @@ from supervision.utils.image import (
     overlay_image,
     scale_image,
 )
-from supervision.utils.internal import deprecated
 
 CV2_FONT = cv2.FONT_HERSHEY_SIMPLEX
 
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index f50c6190..81f0e75f 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -9,12 +9,6 @@ from supervision.config import (
     CLASS_NAME_DATA_FIELD,
     ORIENTED_BOX_COORDINATES,
 )
-from supervision.detection.vlm import (
-    LMM,
-    from_florence_2,
-    from_paligemma,
-    validate_vlm_parameters, VLM,
-)
 from supervision.detection.overlap_filter import (
     box_non_max_merge,
     box_non_max_suppression,
@@ -38,8 +32,15 @@ from supervision.detection.utils import (
     process_roboflow_result,
     xywh_to_xyxy,
 )
+from supervision.detection.vlm import (
+    LMM,
+    VLM,
+    from_florence_2,
+    from_paligemma,
+    validate_vlm_parameters,
+)
 from supervision.geometry.core import Position
-from supervision.utils.internal import get_instance_variables, deprecated
+from supervision.utils.internal import deprecated, get_instance_variables
 from supervision.validators import validate_detections_fields
 
 
@@ -845,7 +846,7 @@ class Detections:
         lmm_to_vlm = {
             LMM.PALIGEMMA: VLM.PALIGEMMA,
             LMM.FLORENCE_2: VLM.FLORENCE_2,
-            LMM.QWEN_2_5_VL: VLM.QWEN_2_5_VL
+            LMM.QWEN_2_5_VL: VLM.QWEN_2_5_VL,
         }
 
         if isinstance(lmm, LMM):
@@ -869,7 +870,9 @@ class Detections:
         return cls.from_vlm(vlm=vlm, result=result, **kwargs)
 
     @classmethod
-    def from_vlm(cls, vlm: Union[VLM, str], result: Union[str, dict], **kwargs: Any) -> Detections:
+    def from_vlm(
+        cls, vlm: Union[VLM, str], result: Union[str, dict], **kwargs: Any
+    ) -> Detections:
         vlm = validate_vlm_parameters(vlm, result, kwargs)
 
         if vlm == VLM.PALIGEMMA: