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docs/en/datasets/detect/coco8.md
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@ -8,7 +8,7 @@ keywords: COCO8, Ultralytics, dataset, object detection, YOLOv8, training, valid
## Introduction
[Ultralytics](https://ultralytics.com) COCO8 is a small, but versatile object detection dataset composed of the first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets.
[Ultralytics](https://www.ultralytics.com/) COCO8 is a small, but versatile object detection dataset composed of the first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets.
<p align="center">
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@ -21,7 +21,7 @@ keywords: COCO8, Ultralytics, dataset, object detection, YOLOv8, training, valid
<strong>Watch:</strong> Ultralytics COCO Dataset Overview
</p>
This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics).
This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com/) and [YOLOv8](https://github.com/ultralytics/ultralytics).
## Dataset YAML
@ -124,7 +124,7 @@ For a comprehensive list of available arguments, refer to the model [Training](.
### Why should I use Ultralytics HUB for managing my COCO8 training?
Ultralytics HUB is an all-in-one web tool designed to simplify the training and deployment of YOLO models, including the Ultralytics YOLOv8 models on the COCO8 dataset. It offers cloud training, real-time tracking, and seamless dataset management. HUB allows you to start training with a single click and avoids the complexities of manual setups. Discover more about [Ultralytics HUB](https://hub.ultralytics.com) and its benefits.
Ultralytics HUB is an all-in-one web tool designed to simplify the training and deployment of YOLO models, including the Ultralytics YOLOv8 models on the COCO8 dataset. It offers cloud training, real-time tracking, and seamless dataset management. HUB allows you to start training with a single click and avoids the complexities of manual setups. Discover more about [Ultralytics HUB](https://hub.ultralytics.com/) and its benefits.
### What are the benefits of using mosaic augmentation in training with the COCO8 dataset?

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docs/en/datasets/detect/roboflow-100.md
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@ -95,7 +95,7 @@ For more ideas and inspiration on real-world applications, be sure to check out
## Usage
The Roboflow 100 dataset is available on both [GitHub](https://github.com/roboflow/roboflow-100-benchmark) and [Roboflow Universe](https://universe.roboflow.com/roboflow-100).
The Roboflow 100 dataset is available on both [GitHub](https://github.com/roboflow/roboflow-100-benchmark) and [Roboflow Universe](https://universe.roboflow.com/roboflow-100?ref=ultralytics).
You can access it directly from the Roboflow 100 GitHub repository. In addition, on Roboflow Universe, you have the flexibility to download individual datasets by simply clicking the export button within each dataset.
@ -197,7 +197,7 @@ This setup allows for extensive and varied testing of models across different re
### How do I access and download the Roboflow 100 dataset?
The **Roboflow 100** dataset is accessible on [GitHub](https://github.com/roboflow/roboflow-100-benchmark) and [Roboflow Universe](https://universe.roboflow.com/roboflow-100). You can download the entire dataset from GitHub or select individual datasets on Roboflow Universe using the export button.
The **Roboflow 100** dataset is accessible on [GitHub](https://github.com/roboflow/roboflow-100-benchmark) and [Roboflow Universe](https://universe.roboflow.com/roboflow-100?ref=ultralytics). You can download the entire dataset from GitHub or select individual datasets on Roboflow Universe using the export button.
### What should I include when citing the Roboflow 100 dataset in my research?