Fix URL (#13408)

* Fix URL

Signed-off-by: Glenn Jocher <[email protected]>

* Update format.yml

Signed-off-by: Glenn Jocher <[email protected]>

---------

Signed-off-by: Glenn Jocher <[email protected]>

.github/workflows/format.yml

@@ -31,7 +31,7 @@ jobs:
 
             If this is a 🐛 Bug Report, please provide a **minimum reproducible example** to help us debug it.
 
-            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://docs.ultralytics.com/guides/model-training-tips//).
+            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://docs.ultralytics.com/guides/model-training-tips/).
 
             ## Requirements
 
@@ -56,14 +56,3 @@ jobs:
             <a href="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg" alt="YOLOv5 CI"></a>
 
             If this badge is green, all [YOLOv5 GitHub Actions](https://github.com/ultralytics/yolov5/actions) Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 [training](https://github.com/ultralytics/yolov5/blob/master/train.py), [validation](https://github.com/ultralytics/yolov5/blob/master/val.py), [inference](https://github.com/ultralytics/yolov5/blob/master/detect.py), [export](https://github.com/ultralytics/yolov5/blob/master/export.py) and [benchmarks](https://github.com/ultralytics/yolov5/blob/master/benchmarks.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit.
-
-            ## Introducing YOLOv8 🚀
-
-            We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - [YOLOv8](https://github.com/ultralytics/ultralytics) 🚀!
-
-            Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.
-
-            Check out our [YOLOv8 Docs](https://docs.ultralytics.com/) for details and get started with:
-            ```bash
-            pip install ultralytics
-            ```