diff --git a/docs/en/guides/triton-inference-server.md b/docs/en/guides/triton-inference-server.md
index 0151cc07..67d419bf 100644
--- a/docs/en/guides/triton-inference-server.md
+++ b/docs/en/guides/triton-inference-server.md
@@ -48,6 +48,16 @@ from ultralytics import YOLO
 # Load a model
 model = YOLO("yolo11n.pt")  # load an official model
 
+# Retreive metadata during export
+metadata = []
+
+
+def export_cb(exporter):
+    metadata.append(exporter.metadata)
+
+
+model.add_callback("on_export_end", export_cb)
+
 # Export the model
 onnx_file = model.export(format="onnx", dynamic=True)
 ```
@@ -107,7 +117,13 @@ The Triton Model Repository is a storage location where Triton can access and lo
         }
       }
     }
-    """
+    parameters {
+      key: "metadata"
+      value: {
+        string_value: "%s"
+      }
+    }
+    """ % metadata[0]
 
     with open(triton_model_path / "config.pbtxt", "w") as f:
         f.write(data)
diff --git a/ultralytics/__init__.py b/ultralytics/__init__.py
index 790bb406..9d19f6ab 100644
--- a/ultralytics/__init__.py
+++ b/ultralytics/__init__.py
@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.3.43"
+__version__ = "8.3.44"
 
 import os
 
diff --git a/ultralytics/nn/autobackend.py b/ultralytics/nn/autobackend.py
index 8e9b74eb..b6df3753 100644
--- a/ultralytics/nn/autobackend.py
+++ b/ultralytics/nn/autobackend.py
@@ -462,6 +462,7 @@ class AutoBackend(nn.Module):
             from ultralytics.utils.triton import TritonRemoteModel
 
             model = TritonRemoteModel(w)
+            metadata = model.metadata
 
         # Any other format (unsupported)
         else:
diff --git a/ultralytics/utils/triton.py b/ultralytics/utils/triton.py
index 3f873a6f..cc53ed57 100644
--- a/ultralytics/utils/triton.py
+++ b/ultralytics/utils/triton.py
@@ -66,6 +66,7 @@ class TritonRemoteModel:
         self.np_input_formats = [type_map[x] for x in self.input_formats]
         self.input_names = [x["name"] for x in config["input"]]
         self.output_names = [x["name"] for x in config["output"]]
+        self.metadata = eval(config.get("parameters", {}).get("metadata", {}).get("string_value", "None"))
 
     def __call__(self, *inputs: np.ndarray) -> List[np.ndarray]:
         """