ultralytics 8.0.177 add https://youtube.com/ultralytics videos to Docs (#4875)
Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Muhammad Rizwan Munawar <62513924+RizwanMunawar@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher
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30 changed files with 453 additions and 161 deletions
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@ -6,14 +6,13 @@ keywords: Ultralytics, HUB datasets, YOLO model training, upload datasets, datas
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# HUB Datasets
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Ultralytics HUB datasets are a practical solution for managing and leveraging your custom datasets.
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[Ultralytics HUB](https://hub.ultralytics.com/) datasets are a practical solution for managing and leveraging your custom datasets.
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Once uploaded, datasets can be immediately utilized for model training. This integrated approach facilitates a seamless transition from dataset management to model training, significantly simplifying the entire process.
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## Upload Dataset
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Ultralytics HUB datasets are just like YOLOv5 and YOLOv8 🚀 datasets. They use the same structure and the same label formats to keep
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everything simple.
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Ultralytics HUB datasets are just like YOLOv5 and YOLOv8 🚀 datasets. They use the same structure and the same label formats to keep everything simple.
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Before you upload a dataset to Ultralytics HUB, make sure to **place your dataset YAML file inside the dataset root directory** and that **your dataset YAML, directory and ZIP have the same name**, as shown in the example below, and then zip the dataset directory.
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@ -41,6 +40,7 @@ After zipping your dataset, you should validate it before uploading it to Ultral
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```py
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from ultralytics.hub import check_dataset
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check_dataset('path/to/coco8.zip')
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```
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@ -18,16 +18,22 @@ keywords: Ultralytics HUB, YOLOv5, YOLOv8, model training, model deployment, pre
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</div>
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<br>
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👋 Hello from the [Ultralytics](https://ultralytics.com/) Team! We've been working hard these last few months to
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launch [Ultralytics HUB](https://bit.ly/ultralytics_hub), a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀
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models from one spot!
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👋 Hello from the [Ultralytics](https://ultralytics.com/) Team! We've been working hard these last few months to launch [Ultralytics HUB](https://bit.ly/ultralytics_hub), a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀 models from one spot!
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## Introduction
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HUB is designed to be user-friendly and intuitive, with a drag-and-drop interface that allows users to
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easily upload their data and train new models quickly. It offers a range of pre-trained models and
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templates to choose from, making it easy for users to get started with training their own models. Once a model is
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trained, it can be easily deployed and used for real-time object detection, instance segmentation and classification tasks.
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HUB is designed to be user-friendly and intuitive, with a drag-and-drop interface that allows users to easily upload their data and train new models quickly. It offers a range of pre-trained models and templates to choose from, making it easy for users to get started with training their own models. Once a model is trained, it can be easily deployed and used for real-time object detection, instance segmentation and classification tasks.
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<p align="center">
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<br>
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<iframe width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
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title="YouTube video player" frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</iframe>
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<br>
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<strong>Watch:</strong> Train Your Custom YOLO Models In A Few Clicks with Ultralytics HUB.
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</p>
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We hope that the resources here will help you get the most out of HUB. Please browse the HUB <a href="https://docs.ultralytics.com/hub">Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <a href="https://ultralytics.com/discord">Discord</a> community for questions and discussions!
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@ -1,7 +1,62 @@
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---
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comments: true
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description: Explore integration options for Ultralytics HUB. Currently featuring Roboflow for dataset integration and multiple export formats for your trained models.
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keywords: Ultralytics HUB, Integrations, Roboflow, Dataset, Export, YOLOv5, YOLOv8, ONNX, CoreML, TensorRT, TensorFlow
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---
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# 🚧 Page Under Construction ⚒
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# HUB Integrations
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This page is currently under construction!️ 👷Please check back later for updates. 😃🔜
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🚧 **Under Construction** 🚧
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Welcome to the Integrations guide for [Ultralytics HUB](https://hub.ultralytics.com/)! We are in the process of expanding this section to provide you with comprehensive guidance on integrating your YOLOv5 and YOLOv8 models with various platforms and formats. Currently, Roboflow is our available dataset integration, with a wide range of export integrations for your trained models.
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<p align="center">
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<br>
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<iframe width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
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title="YouTube video player" frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</iframe>
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<br>
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<strong>Watch:</strong> Train Your Custom YOLO Models In A Few Clicks with Ultralytics HUB.
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</p>
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## Available Integrations
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### Dataset Integrations
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- **Roboflow**: Seamlessly import your datasets for training.
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### Export Integrations
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| Format | `format` Argument | Model | Metadata | Arguments |
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|--------------------------------------------------------------------|-------------------|---------------------------|----------|-----------------------------------------------------|
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| [PyTorch](https://pytorch.org/) | - | `yolov8n.pt` | ✅ | - |
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| [TorchScript](https://pytorch.org/docs/stable/jit.html) | `torchscript` | `yolov8n.torchscript` | ✅ | `imgsz`, `optimize` |
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| [ONNX](https://onnx.ai/) | `onnx` | `yolov8n.onnx` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `opset` |
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| [OpenVINO](../integrations/openvino.md) | `openvino` | `yolov8n_openvino_model/` | ✅ | `imgsz`, `half` |
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| [TensorRT](https://developer.nvidia.com/tensorrt) | `engine` | `yolov8n.engine` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `workspace` |
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| [CoreML](https://github.com/apple/coremltools) | `coreml` | `yolov8n.mlpackage` | ✅ | `imgsz`, `half`, `int8`, `nms` |
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| [TF SavedModel](https://www.tensorflow.org/guide/saved_model) | `saved_model` | `yolov8n_saved_model/` | ✅ | `imgsz`, `keras` |
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| [TF GraphDef](https://www.tensorflow.org/api_docs/python/tf/Graph) | `pb` | `yolov8n.pb` | ❌ | `imgsz` |
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| [TF Lite](https://www.tensorflow.org/lite) | `tflite` | `yolov8n.tflite` | ✅ | `imgsz`, `half`, `int8` |
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| [TF Edge TPU](https://coral.ai/docs/edgetpu/models-intro/) | `edgetpu` | `yolov8n_edgetpu.tflite` | ✅ | `imgsz` |
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| [TF.js](https://www.tensorflow.org/js) | `tfjs` | `yolov8n_web_model/` | ✅ | `imgsz` |
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| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz` |
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| [NCNN](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half` |
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## Coming Soon
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- Additional Dataset Integrations
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- Detailed Export Integration Guides
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- Step-by-Step Tutorials for Each Integration
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## Need Immediate Assistance?
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While we're in the process of creating detailed guides:
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- Browse through other [HUB Docs](https://docs.ultralytics.com/hub/) for detailed guides and tutorials.
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- Raise an issue on our [GitHub](https://github.com/ultralytics/hub/) for technical support.
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- Join our [Discord Community](https://ultralytics.com/discord/) for live discussions and community support.
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We appreciate your patience as we work to make this section comprehensive and user-friendly. Stay tuned for updates!
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@ -6,7 +6,7 @@ keywords: Ultralytics, HUB Models, AI model training, model creation, model trai
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# Ultralytics HUB Models
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Ultralytics HUB models provide a streamlined solution for training vision AI models on your custom datasets.
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[Ultralytics HUB](https://hub.ultralytics.com/) models provide a streamlined solution for training vision AI models on your custom datasets.
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The process is user-friendly and efficient, involving a simple three-step creation and accelerated training powered by Utralytics YOLOv8. During training, real-time updates on model metrics are available so that you can monitor each step of the progress. Once training is completed, you can preview your model and easily deploy it to real-world applications. Therefore, Ultralytics HUB offers a comprehensive yet straightforward system for model creation, training, evaluation, and deployment.
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@ -6,7 +6,7 @@ keywords: Ultralytics, HUB projects, Create project, Edit project, Share project
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# Ultralytics HUB Projects
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Ultralytics HUB projects provide an effective solution for consolidating and managing your models. If you are working with several models that perform similar tasks or have related purposes, Ultralytics HUB projects allow you to group these models together.
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[Ultralytics HUB](https://hub.ultralytics.com/) projects provide an effective solution for consolidating and managing your models. If you are working with several models that perform similar tasks or have related purposes, Ultralytics HUB projects allow you to group these models together.
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This creates a unified and organized workspace that facilitates easier model management, comparison and development. Having similar models or various iterations together can facilitate rapid benchmarking, as you can compare their effectiveness. This can lead to faster, more insightful iterative development and refinement of your models.
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@ -1,7 +1,52 @@
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---
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comments: true
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description: Kickstart your journey with Ultralytics HUB. Learn how to train and deploy YOLOv5 and YOLOv8 models in seconds with our Quickstart guide.
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keywords: Ultralytics HUB, Quickstart, YOLOv5, YOLOv8, model training, quick deployment, drag-and-drop interface, real-time object detection
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---
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# 🚧 Page Under Construction ⚒
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# Quickstart Guide for Ultralytics HUB
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This page is currently under construction!️ 👷Please check back later for updates. 😃🔜
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🚧 **Under Construction** 🚧
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Thank you for visiting the Quickstart guide for [Ultralytics HUB](https://hub.ultralytics.com/)! We're currently hard at work building out this page to provide you with step-by-step instructions on how to get up and running with HUB in no time.
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<p align="center">
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<br>
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<iframe width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
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title="YouTube video player" frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</iframe>
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<br>
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<strong>Watch:</strong> Train Your Custom YOLO Models In A Few Clicks with Ultralytics HUB.
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</p>
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In the meantime, here's a brief overview of what you can expect from Ultralytics HUB:
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## What is Ultralytics HUB?
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Ultralytics HUB is your one-stop solution for training and deploying YOLOv5 and YOLOv8 models. It's designed with user experience in mind, featuring a drag-and-drop interface to make uploading data and training new models a breeze. Whether you're a beginner or an experienced machine learning practitioner, HUB has a range of pre-trained models and templates to accelerate your projects.
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## Key Features
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- **User-Friendly Interface**: Simply drag and drop your data to start training.
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- **Pre-Trained Models**: Choose from a selection of pre-trained models to kick-start your projects.
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- **Real-Time Object Detection**: Deploy trained models easily for real-time object detection, instance segmentation, and classification tasks.
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## Coming Soon
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- Detailed Steps to Start Your First Project
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- Guide on Preparing and Uploading Datasets
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- Tutorial on Model Training and Exporting
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- Integration Options and How-To's
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- And much more!
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## Need Help Now?
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While we're polishing this page, feel free to:
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- Browse through other [HUB Docs](https://docs.ultralytics.com/hub/) for detailed guides and tutorials.
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- Raise an issue on our [GitHub](https://github.com/ultralytics/hub/) for technical support.
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- Join our [Discord Community](https://ultralytics.com/discord/) for live discussions and community support.
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Stay tuned! We'll be back soon with more detailed information to help you get the most out of Ultralytics HUB. Thank you for your patience and interest!
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