Update HUB SDK Docs (#13309)

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

docs/en/models/fast-sam.md

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-description: Explore FastSAM, a CNN-based solution for real-time object segmentation in images. Enhanced user interaction, computational efficiency and adaptable across vision tasks.
-keywords: FastSAM, machine learning, CNN-based solution, object segmentation, real-time solution, Ultralytics, vision tasks, image processing, industrial applications, user interaction
+description: Discover FastSAM, a real-time CNN-based solution for segmenting any object in an image. Efficient, competitive, and ideal for various vision tasks.
+keywords: FastSAM, Fast Segment Anything Model, Ultralytics, real-time segmentation, CNN, YOLOv8-seg, object segmentation, image processing, computer vision
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 # Fast Segment Anything Model (FastSAM)

docs/en/models/index.md

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-description: Explore the diverse range of YOLO family, SAM, MobileSAM, FastSAM, YOLO-NAS, YOLO-World and RT-DETR models supported by Ultralytics. Get started with examples for both CLI and Python usage.
-keywords: Ultralytics, documentation, YOLO, SAM, MobileSAM, FastSAM, YOLO-NAS, RT-DETR, YOLO-World, models, architectures, Python, CLI
+description: Discover a variety of models supported by Ultralytics, including YOLOv3 to YOLOv10, NAS, SAM, and RT-DETR for detection, segmentation, and more.
+keywords: Ultralytics, supported models, YOLOv3, YOLOv4, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, SAM, NAS, RT-DETR, object detection, image segmentation, classification, pose estimation, multi-object tracking
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 # Models Supported by Ultralytics

docs/en/models/mobile-sam.md

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-description: Learn more about MobileSAM, its implementation, comparison with the original SAM, and how to download and test it in the Ultralytics framework. Improve your mobile applications today.
-keywords: MobileSAM, Ultralytics, SAM, mobile applications, Arxiv, GPU, API, image encoder, mask decoder, model download, testing method
+description: Discover MobileSAM, a lightweight and fast image segmentation model for mobile applications. Compare its performance with the original SAM and explore its various modes.
+keywords: MobileSAM, image segmentation, lightweight model, fast segmentation, mobile applications, SAM, ViT encoder, Tiny-ViT, Ultralytics
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 ![MobileSAM Logo](https://github.com/ChaoningZhang/MobileSAM/blob/master/assets/logo2.png?raw=true)

docs/en/models/rtdetr.md

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-description: Discover the features and benefits of RT-DETR, Baidu's efficient and adaptable real-time object detector powered by Vision Transformers, including pre-trained models.
-keywords: RT-DETR, Baidu, Vision Transformers, object detection, real-time performance, CUDA, TensorRT, IoU-aware query selection, Ultralytics, Python API, PaddlePaddle
+description: Explore Baidu's RT-DETR, a Vision Transformer-based real-time object detector offering high accuracy and adaptable inference speed. Learn more with Ultralytics.
+keywords: RT-DETR, Baidu, Vision Transformer, real-time object detection, PaddlePaddle, Ultralytics, pre-trained models, AI, machine learning, computer vision
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 # Baidu's RT-DETR: A Vision Transformer-Based Real-Time Object Detector

docs/en/models/sam.md

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-description: Explore the cutting-edge Segment Anything Model (SAM) from Ultralytics that allows real-time image segmentation. Learn about its promptable segmentation, zero-shot performance, and how to use it.
-keywords: Ultralytics, image segmentation, Segment Anything Model, SAM, SA-1B dataset, real-time performance, zero-shot transfer, object detection, image analysis, machine learning
+description: Explore the revolutionary Segment Anything Model (SAM) for promptable image segmentation with zero-shot performance. Discover key features, datasets, and usage tips.
+keywords: Segment Anything, SAM, image segmentation, promptable segmentation, zero-shot performance, SA-1B dataset, advanced architecture, auto-annotation, Ultralytics, pre-trained models, instance segmentation, computer vision, AI, machine learning
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 # Segment Anything Model (SAM)

docs/en/models/yolo-nas.md

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-description: Explore detailed documentation of YOLO-NAS, a superior object detection model. Learn about its features, pre-trained models, usage with Ultralytics Python API, and more.
-keywords: YOLO-NAS, Deci AI, object detection, deep learning, neural architecture search, Ultralytics Python API, YOLO model, pre-trained models, quantization, optimization, COCO, Objects365, Roboflow 100
+description: Discover YOLO-NAS by Deci AI - a state-of-the-art object detection model with quantization support. Explore features, pretrained models, and implementation examples.
+keywords: YOLO-NAS, Deci AI, object detection, deep learning, Neural Architecture Search, Ultralytics, Python API, YOLO model, SuperGradients, pretrained models, quantization, AutoNAC
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 # YOLO-NAS

docs/en/models/yolo-world.md

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-description: Discover YOLO-World, a YOLOv8-based framework for real-time open-vocabulary object detection in images. It enhances user interaction, boosts computational efficiency, and adapts across various vision tasks.
-keywords: YOLO-World, YOLOv8, machine learning, CNN-based framework, object detection, real-time detection, Ultralytics, vision tasks, image processing, industrial applications, user interaction
+description: Explore the YOLO-World Model for efficient, real-time open-vocabulary object detection using Ultralytics YOLOv8 advancements. Achieve top performance with minimal computation.
+keywords: YOLO-World, Ultralytics, open-vocabulary detection, YOLOv8, real-time object detection, machine learning, computer vision, AI, deep learning, model training
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 # YOLO-World Model

docs/en/models/yolov10.md

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-description: Discover YOLOv10, a cutting-edge real-time object detector known for its exceptional speed and accuracy. Learn about NMS-free training, holistic model design, and performance across various scales.
-keywords: YOLOv10, real-time object detection, Tsinghua University, COCO dataset, NMS-free training, efficient architecture, object detection optimization, state-of-the-art AI
+description: Discover YOLOv10, the latest in real-time object detection, eliminating NMS and boosting efficiency. Achieve top performance with a low computational cost.
+keywords: YOLOv10, real-time object detection, NMS-free, deep learning, Tsinghua University, Ultralytics, machine learning, neural networks, performance optimization
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 # YOLOv10: Real-Time End-to-End Object Detection

docs/en/models/yolov3.md

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-description: Get an overview of YOLOv3, YOLOv3-Ultralytics and YOLOv3u. Learn about their key features, usage, and supported tasks for object detection.
-keywords: YOLOv3, YOLOv3-Ultralytics, YOLOv3u, Object Detection, Inference, Training, Ultralytics
+description: Discover YOLOv3 and its variants YOLOv3-Ultralytics and YOLOv3u. Learn about their features, implementations, and support for object detection tasks.
+keywords: YOLOv3, YOLOv3-Ultralytics, YOLOv3u, object detection, Ultralytics, computer vision, AI models, deep learning
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 # YOLOv3, YOLOv3-Ultralytics, and YOLOv3u

docs/en/models/yolov4.md

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-description: Explore our detailed guide on YOLOv4, a state-of-the-art real-time object detector. Understand its architectural highlights, innovative features, and application examples.
-keywords: ultralytics, YOLOv4, object detection, neural network, real-time detection, object detector, machine learning
+description: Explore YOLOv4, a state-of-the-art real-time object detection model by Alexey Bochkovskiy. Discover its architecture, features, and performance.
+keywords: YOLOv4, object detection, real-time detection, Alexey Bochkovskiy, neural networks, machine learning, computer vision
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 # YOLOv4: High-Speed and Precise Object Detection

docs/en/models/yolov5.md

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-description: Discover YOLOv5u, a boosted version of the YOLOv5 model featuring an improved accuracy-speed tradeoff and numerous pre-trained models for various object detection tasks.
-keywords: YOLOv5u, object detection, pre-trained models, Ultralytics, Inference, Validation, YOLOv5, YOLOv8, anchor-free, objectness-free, real-time applications, machine learning
+description: Explore YOLOv5u, an advanced object detection model with optimized accuracy-speed tradeoff, featuring anchor-free Ultralytics head and various pre-trained models.
+keywords: YOLOv5, YOLOv5u, object detection, Ultralytics, anchor-free, pre-trained models, accuracy, speed, real-time detection
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 # YOLOv5

docs/en/models/yolov6.md

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-description: Explore Meituan YOLOv6, a state-of-the-art object detection model striking a balance between speed and accuracy. Dive into features, pre-trained models, and Python usage.
-keywords: Meituan YOLOv6, object detection, Ultralytics, YOLOv6 docs, Bi-directional Concatenation, Anchor-Aided Training, pretrained models, real-time applications
+description: Explore Meituan YOLOv6, a top-tier object detector balancing speed and accuracy. Learn about its unique features and performance metrics on Ultralytics Docs.
+keywords: Meituan YOLOv6, object detection, real-time applications, BiC module, Anchor-Aided Training, COCO dataset, high-performance models, Ultralytics Docs
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 # Meituan YOLOv6

docs/en/models/yolov7.md

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-description: Explore the YOLOv7, a real-time object detector. Understand its superior speed, impressive accuracy, and unique trainable bag-of-freebies optimization focus.
-keywords: YOLOv7, real-time object detector, state-of-the-art, Ultralytics, MS COCO dataset, model re-parameterization, dynamic label assignment, extended scaling, compound scaling
+description: Discover YOLOv7, the breakthrough real-time object detector with top speed and accuracy. Learn about key features, usage, and performance metrics.
+keywords: YOLOv7, real-time object detection, Ultralytics, AI, computer vision, model training, object detector
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 # YOLOv7: Trainable Bag-of-Freebies

docs/en/models/yolov8.md

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-description: Explore the thrilling features of YOLOv8, the latest version of our real-time object detector! Learn how advanced architectures, pre-trained models and optimal balance between accuracy & speed make YOLOv8 the perfect choice for your object detection tasks.
-keywords: YOLOv8, Ultralytics, real-time object detector, pre-trained models, documentation, object detection, YOLO series, advanced architectures, accuracy, speed
+description: Discover YOLOv8, the latest advancement in real-time object detection, optimizing performance with an array of pre-trained models for diverse tasks.
+keywords: YOLOv8, real-time object detection, YOLO series, Ultralytics, computer vision, advanced object detection, AI, machine learning, deep learning
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 # YOLOv8

docs/en/models/yolov9.md

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-description: Discover YOLOv9, the latest addition to the real-time object detection arsenal, leveraging Programmable Gradient Information and GELAN architecture for unparalleled performance.
-keywords: YOLOv9, real-time object detection, Programmable Gradient Information, GELAN architecture, Ultralytics, MS COCO dataset, open-source, lightweight model, computer vision, AI
+description: Explore YOLOv9, the latest leap in real-time object detection, featuring innovations like PGI and GELAN, and achieving new benchmarks in efficiency and accuracy.
+keywords: YOLOv9, object detection, real-time, PGI, GELAN, deep learning, MS COCO, AI, neural networks, model efficiency, accuracy, Ultralytics
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 # YOLOv9: A Leap Forward in Object Detection Technology