Update HUB SDK Docs (#13309)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/modes/benchmark.md

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-description: Learn how to profile speed and accuracy of YOLOv8 across various export formats; get insights on mAP50-95, accuracy_top5 metrics, and more.
-keywords: Ultralytics, YOLOv8, benchmarking, speed profiling, accuracy profiling, mAP50-95, accuracy_top5, ONNX, OpenVINO, TensorRT, YOLO export formats
+description: Learn how to evaluate your YOLOv8 model's performance in real-world scenarios using benchmark mode. Optimize speed, accuracy, and resource allocation across export formats.
+keywords: model benchmarking, YOLOv8, Ultralytics, performance evaluation, export formats, ONNX, TensorRT, OpenVINO, CoreML, TensorFlow, optimization, mAP50-95, inference time
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 # Model Benchmarking with Ultralytics YOLO

docs/en/modes/export.md

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-description: Step-by-step guide on exporting your YOLOv8 models to various format like ONNX, TensorRT, CoreML and more for deployment. Explore now!.
-keywords: YOLO, YOLOv8, Ultralytics, Model export, ONNX, TensorRT, CoreML, TensorFlow SavedModel, OpenVINO, PyTorch, export model
+description: Learn how to export your YOLOv8 model to various formats like ONNX, TensorRT, and CoreML. Achieve maximum compatibility and performance.
+keywords: YOLOv8, Model Export, ONNX, TensorRT, CoreML, Ultralytics, AI, Machine Learning, Inference, Deployment
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 # Model Export with Ultralytics YOLO

docs/en/modes/index.md

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-description: From training to tracking, make the most of YOLOv8 with Ultralytics. Get insights and examples for each supported mode including validation, export, and benchmarking.
-keywords: Ultralytics, YOLOv8, Machine Learning, Object Detection, Training, Validation, Prediction, Export, Tracking, Benchmarking
+description: Discover the diverse modes of Ultralytics YOLOv8, including training, validation, prediction, export, tracking, and benchmarking. Maximize model performance and efficiency.
+keywords: Ultralytics, YOLOv8, machine learning, model training, validation, prediction, export, tracking, benchmarking, object detection
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 # Ultralytics YOLOv8 Modes

docs/en/modes/predict.md

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-description: Discover how to use YOLOv8 predict mode for various tasks. Learn about different inference sources like images, videos, and data formats.
-keywords: Ultralytics, YOLOv8, predict mode, inference sources, prediction tasks, streaming mode, image processing, video processing, machine learning, AI
+description: Harness the power of Ultralytics YOLOv8 for real-time, high-speed inference on various data sources. Learn about predict mode, key features, and practical applications.
+keywords: Ultralytics, YOLOv8, model prediction, inference, predict mode, real-time inference, computer vision, machine learning, streaming, high performance
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 # Model Prediction with Ultralytics YOLO

docs/en/modes/track.md

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-description: Learn how to use Ultralytics YOLO for object tracking in video streams. Guides to use different trackers and customise tracker configurations.
-keywords: Ultralytics, YOLO, object tracking, video streams, BoT-SORT, ByteTrack, Python guide, CLI guide
+description: Discover efficient, flexible, and customizable multi-object tracking with Ultralytics YOLO. Learn to track real-time video streams with ease.
+keywords: multi-object tracking, Ultralytics YOLO, video analytics, real-time tracking, object detection, AI, machine learning
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 # Multi-Object Tracking with Ultralytics YOLO

docs/en/modes/train.md

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-description: Step-by-step guide to train YOLOv8 models with Ultralytics YOLO including examples of single-GPU and multi-GPU training
-keywords: Ultralytics, YOLOv8, YOLO, object detection, train mode, custom dataset, GPU training, multi-GPU, hyperparameters, CLI examples, Python examples
+description: Learn how to efficiently train object detection models using YOLOv8 with comprehensive instructions on settings, augmentation, and hardware utilization.
+keywords: Ultralytics, YOLOv8, model training, deep learning, object detection, GPU training, dataset augmentation, hyperparameter tuning, model performance, M1 M2 training
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 # Model Training with Ultralytics YOLO

docs/en/modes/val.md

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-description: Guide for Validating YOLOv8 Models. Learn how to evaluate the performance of your YOLO models using validation settings and metrics with Python and CLI examples.
-keywords: Ultralytics, YOLO Docs, YOLOv8, validation, model evaluation, hyperparameters, accuracy, metrics, Python, CLI
+description: Learn how to validate your YOLOv8 model with precise metrics, easy-to-use tools, and custom settings for optimal performance.
+keywords: Ultralytics, YOLOv8, model validation, machine learning, object detection, mAP metrics, Python API, CLI
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 # Model Validation with Ultralytics YOLO