docs: 📝 readme links are updated

README.md

@@ -29,7 +29,7 @@ model-index:
 ---
 <div align="center">
   <p>
-    <a href="http://platform.ultralytics.com/" target="_blank">
+    <a href="https://platform.ultralytics.com/?utm_source=huggingface&utm_medium=referral&utm_campaign=yolo26&utm_content=banner" target="_blank">
       <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="Ultralytics YOLO banner"></a>
   </p>
   <p style="margin: 3px 0;">
@@ -58,7 +58,7 @@ Find detailed documentation in the [Ultralytics Docs](https://docs.ultralytics.c
 
 Request an Enterprise License for commercial use at [Ultralytics Licensing](https://www.ultralytics.com/license).
 
-<a href="https://platform.ultralytics.com/ultralytics/yolo26" target="_blank">
+<a href="https://docs.ultralytics.com/models/yolo26/?utm_source=huggingface&utm_medium=referral&utm_campaign=yolo26&utm_content=benchmark_graph" target="_blank">
   <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/refs/heads/main/yolo/performance-comparison.png" alt="YOLO26 performance plots">
 </a>
 <div align="center" style="display: flex; flex-wrap: wrap; justify-content: center; align-items: center; gap: 20px;">
@@ -150,7 +150,7 @@ Discover more examples in the YOLO [Python Docs](https://docs.ultralytics.com/us
 
 ## <div align="center">✨ Models</div>
 
-Ultralytics supports a wide range of YOLO models, from early versions like [YOLOv3](https://docs.ultralytics.com/models/yolov3/) to the latest [Ultralytics YOLO26](https://platform.ultralytics.com/ultralytics/yolo26). The tables below showcase Ultralytics YOLO26 models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco/) dataset for [Detection](https://docs.ultralytics.com/tasks/detect/), [Segmentation](https://docs.ultralytics.com/tasks/segment/), and [Pose Estimation](https://docs.ultralytics.com/tasks/pose/). Additionally, [Classification](https://docs.ultralytics.com/tasks/classify/) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/) dataset are available. [Tracking](https://docs.ultralytics.com/modes/track/) mode is compatible with all Detection, Segmentation, and Pose models. All [Models](https://docs.ultralytics.com/models/) are automatically downloaded from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) upon first use.
+Ultralytics supports a wide range of YOLO models, from early versions like [YOLOv3](https://docs.ultralytics.com/models/yolov3/) to the latest [Ultralytics YOLO26](https://platform.ultralytics.com/ultralytics/yolo26?utm_source=huggingface&utm_medium=referral&utm_campaign=yolo26&utm_content=contextual_model_link). The tables below showcase [Ultralytics YOLO26](https://platform.ultralytics.com/ultralytics/yolo26?utm_source=huggingface&utm_medium=referral&utm_campaign=yolo26&utm_content=contextual_model_link) models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco/) dataset for [Detection](https://docs.ultralytics.com/tasks/detect/), [Segmentation](https://docs.ultralytics.com/tasks/segment/), and [Pose Estimation](https://docs.ultralytics.com/tasks/pose/). Additionally, [Classification](https://docs.ultralytics.com/tasks/classify/) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/) dataset are available. [Tracking](https://docs.ultralytics.com/modes/track/) mode is compatible with all Detection, Segmentation, and Pose models. All [Models](https://docs.ultralytics.com/models/) are automatically downloaded from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) upon first use.
 
 <img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/main/im/banner-tasks.png" alt="Ultralytics YOLO supported tasks">
 
@@ -249,9 +249,9 @@ Our key integrations with leading AI platforms extend the functionality of Ultra
 <br>
 <br>
 
-| <a href="https://platform.ultralytics.com/ultralytics/yolo26"><img src="https://cdn.jsdelivr.net/gh/ultralytics/assets@main/logo/Ultralytics-logomark-color.png" width="30%" alt="Ultralytics Platform logo"></a><br>Ultralytics Platform 🌟 | <a href="https://docs.ultralytics.com/integrations/weights-biases/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-wb.png" width="40%" alt="Weights & Biases logo"></a><br>Weights & Biases | <a href="https://docs.ultralytics.com/integrations/comet/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-comet.png" width="40%" alt="Comet ML logo"></a><br>Comet | <a href="https://docs.ultralytics.com/integrations/neural-magic/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-neuralmagic.png" width="40%" alt="Neural Magic logo"></a><br>Neural Magic |
+| <a href="https://platform.ultralytics.com/ultralytics/yolo26?utm_source=huggingface&utm_medium=referral&utm_campaign=yolo26&utm_content=contextual_model_link"><img src="https://cdn.jsdelivr.net/gh/ultralytics/assets@main/logo/Ultralytics-logomark-color.png" width="30%" alt="Ultralytics Platform logo"></a><br>Ultralytics Platform 🌟 | <a href="https://docs.ultralytics.com/integrations/weights-biases/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-wb.png" width="40%" alt="Weights & Biases logo"></a><br>Weights & Biases | <a href="https://docs.ultralytics.com/integrations/comet/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-comet.png" width="40%" alt="Comet ML logo"></a><br>Comet | <a href="https://docs.ultralytics.com/integrations/neural-magic/"><img src="https://github.com/ultralytics/assets/raw/main/partners/logo-neuralmagic.png" width="40%" alt="Neural Magic logo"></a><br>Neural Magic |
 | :---: | :---: | :---: | :---: |
-| Streamline Ultralytics YOLO workflows: Label, train, and deploy effortlessly with [Ultralytics Platform](https://platform.ultralytics.com/ultralytics/yolo26). Try now! | Track experiments, hyperparameters, and results with [Weights & Biases](https://docs.ultralytics.com/integrations/weights-biases/). | Free forever, [Comet ML](https://docs.ultralytics.com/integrations/comet/) lets you save Ultralytics YOLO models, resume training, and interactively visualize predictions. | Run Ultralytics YOLO inference up to 6x faster with [Neural Magic DeepSparse](https://docs.ultralytics.com/integrations/neural-magic/). |
+| Streamline Ultralytics YOLO workflows: Label, train, and deploy effortlessly with [Ultralytics Platform](https://platform.ultralytics.com/ultralytics/yolo26?utm_source=huggingface&utm_medium=referral&utm_campaign=yolo26&utm_content=contextual_model_link). Try now! | Track experiments, hyperparameters, and results with [Weights & Biases](https://docs.ultralytics.com/integrations/weights-biases/). | Free forever, [Comet ML](https://docs.ultralytics.com/integrations/comet/) lets you save Ultralytics YOLO models, resume training, and interactively visualize predictions. | Run Ultralytics YOLO inference up to 6x faster with [Neural Magic DeepSparse](https://docs.ultralytics.com/integrations/neural-magic/). |
 
 ## <div align="center">🤝 Contribute</div>