docs: Update label-studio-ml-backend docs (#6450)

Co-authored-by: makseq <[email protected]>
Co-authored-by: Caitlin Wheeless <[email protected]>
Co-authored-by: caitlinwheeless <[email protected]>

docs/source/tutorials/yolo.md

@@ -214,13 +214,23 @@ Here is an example of a prompt for this. It includes 1000 labels from YOLOv8 cla
 
 </details>
 
-## YOLOv5 and other YOLO versions
+## Supported YOLO Versions: YOLOv5, YOLO11, and others
 
-YOLOv8 models have been successfully tested with this ML backend.
+- **YOLOv5**: This model is supported for object detection tasks. Make sure to specify `model_path="yolov5nu.pt"` (don't forget the **`u`**) to use the YOLOv5 model.
+
+- **YOLOv8**: These models have been successfully tested with the current ML backend. Check the full list of [v8 models here](https://docs.ultralytics.com/models/yolov8/#supported-tasks-and-modes).
+
+- **YOLO11**: YOLO11 models have also been successfully tested with this ML backend. Check the full list of [v11 models here](https://docs.ultralytics.com/models/yolo11/#supported-tasks-and-modes).
+
+    **Warning 1**: You must upgrade the `ultralytics` package to the latest version (`pip install -U ultralytics`) or rebuild the ML backend Docker from scratch (`docker-compose build --no-cache`) if you used it before the latest Ultralytics update on **Monday, September 30, 2024**.
+
+    **Warning 2**: YOLO11 models do not use the `v` in their naming convention. For example, use **`yolo11n.pt`** instead of `yolov11n.pt`, unlike the naming convention in YOLOv8.
+
+- For a full list of supported YOLO versions and models, refer to the Ultralytics documentation:
+  [Ultralytics Supported YOLO Models](https://docs.ultralytics.com/models/)
+
+    **Note**: Some YOLO models listed in the Ultralytics documentation have not been tested with this ML backend, but they might still work.
 
-Attempts to run YOLOv5 were unsuccessful without modifications. 
-It may be possible to run it by applying some changes, such as installing additional dependencies. 
-The same applies to other YOLO models.
 
 ## Your own custom YOLO models
 
@@ -239,6 +249,22 @@ You can load your own YOLO labels using the following steps:
 You can integrate your own custom-trained YOLOv8 models with the YOLO ML backend for Label Studio. 
 Follow these detailed steps to set up your custom model in the ML backend Docker:
 
+### Step 0: Install Label Studio and clone this Github repository
+
+1. Install and run Label Studio (or see [more ways here](https://labelstud.io/guide/install)). 
+
+```
+pip install label-studio
+label-studio
+```
+
+2. Clone the Label Studio ML backend repository and go to the `yolo` example folder:
+
+```
+git clone https://github.com/HumanSignal/label-studio-ml-backend.git
+cd label-studio-ml-backend/examples/yolo
+```
+
 ### Step 1: Prepare your custom YOLOv8 model
 
 Ensure that your custom YOLOv8 model is saved as a `.pt` file, which is the standard format for PyTorch models. 
@@ -804,7 +830,6 @@ There are two modes available:
 - **Trainable:** In the [trainable mode](https://github.com/HumanSignal/label-studio-ml-backend/blob/master/label_studio_ml/examples/yolo/README_TIMELINE_LABELS.md), the model can be trained on custom labels and annotations submitted in Label Studio using few-shot learning as training is performed on a small number of annotations.  
 
 <iframe width="560" height="315" src="https://www.youtube.com/embed/tfMn5q1tqKI?si=T5FhfImJEnWRSqpY" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
-<br/>
 
 ### Labeling config
 
@@ -965,4 +990,4 @@ LOG_LEVEL=DEBUG python cli.py --ls-url http://localhost:8080 --ls-api-key YOUR_A
 
 ## For developers
 
-The architecture of the project and development guidelines are described in the [README_DEVELOP.md](https://github.com/HumanSignal/label-studio-ml-backend/blob/master/label_studio_ml/examples/yolo/README_DEVELOP.md) file.
+The architecture of the project and development guidelines are described in the [README_DEVELOP.md](https://github.com/HumanSignal/label-studio-ml-backend/blob/master/label_studio_ml/examples/yolo/README_DEVELOP.md) file.