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docs: Create docs for cogstack community edition
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docs/docs/cogstack-ce/_index.md

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- [Deployment](../platform/deployment/_index.md)
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- [CogStack CE Helm chart (install + customization)](../platform/deployment/helm/charts/cogstack-ce-helm.md)
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## Models
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The default installation comes with basic models that are just for demo purposes.
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There are public models available, that will require a NIH profile or UMLS license. See [MedCAT](https://github.com/CogStack/cogstack-nlp/tree/main/medcat-v2) documentation for how to get these models.
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!!! tip
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For access to high performing models trained on real world clinical datasets, contact us
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## Next Steps
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After setting up and trying CogStack Community edition, you can look into the details and wider tools in the platform

docs/docs/cogstack-ce/tutorial/quickstart-installation.md

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This tutorial installs CogStack CE using Helm, sets up port-forwarding, and opens the bundled JupyterHub in your browser.
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The install should take around 15 minutes, and by the end of this tutorial you will have a fully working and integrated CogStack environment that you can start using.
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## Prerequisites
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- A Kubernetes cluster
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This command will install Cogstack community edition with all the default values.
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!!! warning
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For brand new installations, this might take a while, so expect up to 15 minutes. It needs to download many GB of docker images first and then startup processes.
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Once the initial installation is done, then any updates should be significantly faster.
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The defaults are set for a production-ready environment. See [Deployment](../../platform/deployment/_index.md) for detailed deployment information and customization options.
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For brand new installations, this might take a while, so expect up to 15 minutes. It needs to download many GB of docker images first and then startup processes.
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Once the initial installation is done, then any updates should be significantly faster.
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The defaults are set for a production-ready environment. See [Deployment](../../platform/deployment/_index.md) for detailed deployment information and customization options.
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## Port-forward and open JupyterHub

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