hub/quickstart/

[giscus[bot]]

hub/quickstart/

Get started with Ultralytics HUB! Learn to upload datasets, train YOLO models, and manage projects easily with our user-friendly platform.

https://docs.ultralytics.com/hub/quickstart/

[sjocnjfjd]

请问如果我想修改模型的参数或者是引入注意力机制我应该怎么操作或者是从哪里找源代码呢？

[glenn-jocher]

To modify model parameters or introduce attention mechanisms, you can explore the source code in the Ultralytics GitHub repository. For detailed guidance, consider reviewing the model configuration files and relevant sections in the documentation.

[UltralyticsAssistant]

👋 Hello, thank you for reaching out about Ultralytics HUB 🚀! It's exciting to see your interest in getting started with our platform. We suggest exploring the Docs, especially the HUB Quickstart Guide, to help you upload datasets, train YOLO models, and manage projects effectively.

If you encounter any issues or have further questions, please specify if it's a 🐛 bug report or a custom training ❓ question. Providing a minimum reproducible example for bug reports or detailed information, like dataset examples and training logs for questions, will help us assist you better.

While this is an automated response to guide you, an Ultralytics engineer will be along shortly to provide additional support. 😊

Join our community for more engaging discussions: check Discord for real-time chat 🎧, explore our Discourse for in-depth discussions, or visit our Subreddit.

Upgrade

Make sure to upgrade to the latest ultralytics package and all requirements in a Python>=3.8 environment with PyTorch>=1.8 to ensure you're working with the latest features and fixes:

pip install -U ultralytics

Environments

Explore our pre-configured environments to run YOLO effortlessly:

• Notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. Visit AWS Quickstart Guide
• Docker Image. Access the Docker Quickstart Guide

Status

Our CI badge reflects the current status of all Ultralytics CI tests. When green, it indicates that tests across all YOLO Modes and Tasks on macOS, Windows, and Ubuntu are passing. Rest assured, we're ensuring quality and reliability continuously!