Docs updates for HUB, YOLOv4, YOLOv7, NAS (#3174)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/modes/benchmark.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: Benchmark mode compares speed and accuracy of various YOLOv8 export formats like ONNX or OpenVINO. Optimize formats for speed or accuracy.
+keywords: YOLOv8, Benchmark Mode, Export Formats, ONNX, OpenVINO, TensorRT, Ultralytics Docs
 ---
 
 <img width="1024" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png">

docs/modes/export.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: 'Export mode: Create a deployment-ready YOLOv8 model by converting it to various formats. Export to ONNX or OpenVINO for up to 3x CPU speedup.'
+keywords: ultralytics docs, YOLOv8, export YOLOv8, YOLOv8 model deployment, exporting YOLOv8, ONNX, OpenVINO, TensorRT, CoreML, TF SavedModel, PaddlePaddle, TorchScript, ONNX format, OpenVINO format, TensorRT format, CoreML format, TF SavedModel format, PaddlePaddle format
 ---
 
 <img width="1024" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png">

docs/modes/index.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: Use Ultralytics YOLOv8 Modes (Train, Val, Predict, Export, Track, Benchmark) to train, validate, predict, track, export or benchmark.
+keywords: yolov8, yolo, ultralytics, training, validation, prediction, export, tracking, benchmarking, real-time object detection, object tracking
 ---
 
 # Ultralytics YOLOv8 Modes

docs/modes/predict.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: Get started with YOLOv8 Predict mode and input sources. Accepts various input sources such as images, videos, and directories.
+keywords: YOLOv8, predict mode, generator, streaming mode, input sources, video formats, arguments customization
 ---
 
 <img width="1024" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png">
@@ -300,4 +301,4 @@ Here's a Python script using OpenCV (cv2) and YOLOv8 to run inference on video f
     # Release the video capture object and close the display window
     cap.release()
     cv2.destroyAllWindows()
-    ```
+    ```

docs/modes/track.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: Explore YOLOv8n-based object tracking with Ultralytics' BoT-SORT and ByteTrack. Learn configuration, usage, and customization tips.
+keywords: object tracking, YOLO, trackers, BoT-SORT, ByteTrack
 ---
 
 <img width="1024" src="https://user-images.githubusercontent.com/26833433/243418637-1d6250fd-1515-4c10-a844-a32818ae6d46.png">
@@ -97,5 +98,4 @@ any configurations(expect the `tracker_type`) you need to.
         ```
 
 Please refer to [ultralytics/tracker/cfg](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/tracker/cfg)
-page
-
+page

docs/modes/train.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: Learn how to train custom YOLOv8 models on various datasets, configure hyperparameters, and use Ultralytics' YOLO for seamless training.
+keywords: YOLOv8, train mode, train a custom YOLOv8 model, hyperparameters, train a model, Comet, ClearML, TensorBoard, logging, loggers
 ---
 
 <img width="1024" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png">

docs/modes/val.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 description: Validate and improve YOLOv8n model accuracy on COCO128 and other datasets using hyperparameter & configuration tuning, in Val mode.
+keywords: Ultralytics, YOLO, YOLOv8, Val, Validation, Hyperparameters, Performance, Accuracy, Generalization, COCO, Export Formats, PyTorch
 ---
 
 <img width="1024" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png">