Merge pull request #208 from stan-dev/homepage-formatting

Alt. homepage formatting

index.qmd

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 # Stan: Software for Bayesian Data Analysis
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 ### Bayesian Modeling
 
 Stan enables sophisticated statistical modeling using Bayesian inference, allowing for more accurate and interpretable results in complex data scenarios.
@@ -45,44 +36,32 @@ Interfaces for Python, Julia, R, and the Unix shell make it easy to use Stan in
 on  laptops, clusters, or in the cloud.  A rich ecosystem of tools for validation and visualization support
 decision-making and communication.
 
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+::::: {.hero-buttons style="position: relative; display: flex; justify-content: center;"}
 [Get Started](install/){.btn-action-primary .btn-action .btn .btn-success .btn-lg role="button"}
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-## Community Resources
+### Community Resources
 * The Stan [forums](https://discourse.mc-stan.org) provide support for all user levels and topics, from installing software, to writing Stan programs, to advanced Bayesian modeling techniques and methodology.
 
 * Stan's [documentation](https://mc-stan.org/docs), [tutorials](learn-stan/tutorials.qmd), and [case studies](learn-stan/case-studies.qmd) help users learn and use Stan effectively in their own projects.
 The [Prior Choice Recommendations](https://github.com/stan-dev/stan/wiki/Prior-Choice-Recommendations) wiki page provides guidance on appropriate priors for use with Stan.
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+---
 
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-## Developer Resources
+### Developer Resources
 * The [Stan Developer Wiki](https://github.com/stan-dev/stan/wiki)
 
 * The [Stan Forums Developers category](https://discourse.mc-stan.org/c/stan-dev/10)
 
 * The Stan slack channel [mc-stan.slack.com](https://join.slack.com/t/mc-stan/shared_invite/zt-1le4ebi4m-UMtiOkJb4gcS16qz2wIYCw)
 is for informal developer discussions.
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