@@ -4,7 +4,7 @@ A few installation deployment targets are provided below.
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- [ Ray Cluster Using Operator on Openshift] ( #Openshift-Ray-Cluster-Operator )
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- [ Ray Cluster on Openshift] ( #Openshift-Cluster )
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- - [ Ray Cluster on Openshift for Jupyter] ( #Jupyter )
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+ - [ Ray Cluster on Openshift for Jupyter] ( #Ray-with-Open-Data-Hub-on-OpenShift )
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## Openshift Ray Cluster Operator
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@@ -151,9 +151,29 @@ pip3 install -r requirements.txt
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[0, 1, 4, 9]
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```
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- ### Jupyter
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-
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- Jupyter setup demo [Reference repository](https://github.com/erikerlandson/ray-odh-demo)
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+ ### Ray with Open Data Hub on OpenShift
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+
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+ The
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+ [Operate First](https://www.operate-first.cloud/)
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+ project hosts a public
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+ [demonstration](https://www.operate-first.cloud/users/moc-ray-demo/README.md)
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+ of ray-enabled jupyter notebooks, based on the
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+ [Open Data Hub](https://opendatahub.io/)
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+ (ODH) data science platform.
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+ This free ODH environment can be accessed
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+ [here](https://odh.operate-first.cloud/),
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+ and is accessible to anyone with a gmail account via SSO login.
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+
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+ To install a similar Ray integration with CodeFlare onto your own Open Data Hub environment,
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+ follow the instructions on this
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+ [reference repository](https://github.com/erikerlandson/ray-odh-demo).
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+
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+ The container images used in this reference demo were built from
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+ [this repo](https://github.com/erikerlandson/ray-ubi),
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+ and have CodeFlare pre-installed. They include a basic
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+ ["ray-ml" notebook image](https://github.com/erikerlandson/ray-ubi/tree/main/images/ray-ml-notebook)
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+ and a corresponding
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+ [ray-ml worker-node image](https://github.com/erikerlandson/ray-ubi/tree/main/images/ray-ml-ubi).
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### Running examples
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