diff --git a/README.md b/README.md
index 9729982c..eb8aafc6 100644
--- a/README.md
+++ b/README.md
@@ -68,17 +68,17 @@ python app.py
 ## Validation
 [`yolov10n`](https://huggingface.co/jameslahm/yolov10n)  [`yolov10s`](https://huggingface.co/jameslahm/yolov10s)  [`yolov10m`](https://huggingface.co/jameslahm/yolov10m)  [`yolov10b`](https://huggingface.co/jameslahm/yolov10b)  [`yolov10l`](https://huggingface.co/jameslahm/yolov10l)  [`yolov10x`](https://huggingface.co/jameslahm/yolov10x)  
 ```
-wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10s.pt
-yolo val model=yolov10n/s/m/b/l/x.pt data=coco.yaml batch=256
+yolo val model=jameslahm/yolov10{n/s/m/b/l/x} data=coco.yaml batch=256
 ```
 
 Or
 ```python
 from ultralytics import YOLOv10
 
-model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
-# or
 model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
+# or
+# wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10{n/s/m/b/l/x}.pt
+model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
 
 model.val(data='coco.yaml', batch=256)
 ```
@@ -96,9 +96,10 @@ from ultralytics import YOLOv10
 model = YOLOv10()
 # If you want to finetune the model with pretrained weights, you could load the 
 # pretrained weights like below
-# model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
-# or
 # model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
+# or
+# wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10{n/s/m/b/l/x}.pt
+# model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
 
 model.train(data='coco.yaml', epochs=500, batch=256, imgsz=640)
 ```
@@ -118,16 +119,17 @@ model.push_to_hub("<your-hf-username-or-organization/yolov10-finetuned-crop-dete
 ## Prediction
 Note that a smaller confidence threshold can be set to detect smaller objects or objects in the distance. Please refer to [here](https://github.com/THU-MIG/yolov10/issues/136) for details.
 ```
-yolo predict model=yolov10n/s/m/b/l/x.pt
+yolo predict model=jameslahm/yolov10{n/s/m/b/l/x}
 ```
 
 Or
 ```python
 from ultralytics import YOLOv10
 
-model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
-# or
 model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
+# or
+# wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10{n/s/m/b/l/x}.pt
+model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
 
 model.predict()
 ```
@@ -135,12 +137,12 @@ model.predict()
 ## Export
 ```
 # End-to-End ONNX
-yolo export model=yolov10n/s/m/b/l/x.pt format=onnx opset=13 simplify
+yolo export model=jameslahm/yolov10{n/s/m/b/l/x} format=onnx opset=13 simplify
 # Predict with ONNX
 yolo predict model=yolov10n/s/m/b/l/x.onnx
 
 # End-to-End TensorRT
-yolo export model=yolov10n/s/m/b/l/x.pt format=engine half=True simplify opset=13 workspace=16
+yolo export model=jameslahm/yolov10{n/s/m/b/l/x} format=engine half=True simplify opset=13 workspace=16
 # or
 trtexec --onnx=yolov10n/s/m/b/l/x.onnx --saveEngine=yolov10n/s/m/b/l/x.engine --fp16
 # Predict with TensorRT
@@ -151,9 +153,10 @@ Or
 ```python
 from ultralytics import YOLOv10
 
-model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
+model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
 # or
-model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}.pt')
+# wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10{n/s/m/b/l/x}.pt
+model = YOLOv10('yolov10{n/s/m/b/l/x}.pt')
 
 model.export(...)
 ```
diff --git a/ultralytics/cfg/__init__.py b/ultralytics/cfg/__init__.py
index 0e081d1c..72681ae6 100644
--- a/ultralytics/cfg/__init__.py
+++ b/ultralytics/cfg/__init__.py
@@ -1,6 +1,7 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
 import contextlib
+import os
 import shutil
 import subprocess
 import sys
@@ -553,7 +554,12 @@ def entrypoint(debug=""):
     elif "yolov10" in stem:
         from ultralytics import YOLOv10
 
-        model = YOLOv10(model)
+        # Special case for the HuggingFace Hub
+        split_path = model.split('/')
+        if len(split_path) == 2 and (not os.path.exists(model)):
+            model = YOLOv10.from_pretrained(model)
+        else:
+            model = YOLOv10(model)
     else:
         from ultralytics import YOLO