How to simplify execution of cloud-native model training & validation with CodeFlare: A HandsOn Demo

Join us for a hands-on demo of the CodeFlare-SDK, an open-source project that simplifies cloud-native data pre-processing, model training and validation with an intuitive Python interface to Ray, PyTorch/TorchX, and Kubernetes. With the CodeFlare-SDK, you can easily manage your cloud resources, submit jobs, and monitor job status, without worrying about the complexities of DevOps and cloud infrastructure. In this demo, Mustafa Eyceoz and Atin Sood will guide you through the CodeFlare-SDK workflow, from resource allocation to ML job submission and monitoring. You will see firsthand how easy it is to train large scale models (foundation models) in the cloud using the CodeFlare-SDK. Don't miss this opportunity to learn how CodeFlare can make cloud-native model training more accessible and manageable for developers.


About Anyscale
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Anyscale is the AI Application Platform for developing, running, and scaling AI.

https://www.anyscale.com/

If you're interested in a managed Ray service, check out:
https://www.anyscale.com/signup/

About Ray
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Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads.
https://docs.ray.io/en/latest/


#llm #machinelearning #ray #deeplearning #distributedsystems #python #genai