AI-generated Key Takeaways
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Derm Foundation can be run locally for experimentation with smaller data volumes.
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For production-grade online applications, deploy Derm Foundation as a scalable HTTPS endpoint on Vertex AI.
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Process larger datasets efficiently by launching Derm Foundation as a Vertex AI batch prediction job.
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A research endpoint is available to try out the Derm Foundation online service for research purposes.
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You can contact the project team through GitHub Discussions, GitHub Issues, or email.
You can get started in 4 ways:
Run it locally
Download the model from Hugging Face and run it locally.
This is the recommended option, if you want to experiment with the model and don't need to handle a high volume of data. Our GitHub repository includes a notebook that you can use to explore the model.
Deploy your own online service
Derm Foundation can be deployed as a highly available and scalable HTTPS endpoint on Vertex AI. The easiest way is through Model Garden.
This option is ideal for production-grade, online applications with low latency, high scalability and availability requirements. Refer to Vertex AI's service level agreement (SLA) and pricing model for online predictions.
Read the API specification to learn how to create online clients that interact with the service. A sample notebook is available to help you get started quickly.
For custom requirements, you can also adapt our model serving implementation and host it yourself on any API management system.
Launch a batch job
For larger dataset in a batch workflow, it's best to launch it as a Vertex AI batch prediction job. Note that Vertex AI's SLA and pricing model are different for batch prediction jobs.
Refer to the "Get batch predictions" section in the Quick start with Model Garden notebook to get started.
Try out our online service
You can test out the online service before committing to deploying your own using our research endpoint.
This endpoint is for research purposes only.
Contact
You can reach out in several ways:
- Start or join a conversation on GitHub Discussions.
- File a Feature Request or Bug at GitHub Issues.
- Send us feedback at
hai-def@google.com.