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bulma-clean-theme

Gem Version Gem

This is a clean and simple Jekyll Theme built with the Bulma framework, providing a modern-looking site to start with.

The theme uses Alpine.js for its interactive components, such as mobile navbar and notifications.

Contents

Installation

Add this line to your Jekyll site's Gemfile:

gem "bulma-clean-theme"

And add this line to your Jekyll site's _config.yml:

theme: bulma-clean-theme

If you are deploying to GitHub pages, then you can also install the GitHub Pages gem and use remote_theme instead of theme in your _config.yml. Note that the GitHub Pages gem requires Jekyll version 3.9.

# With GitHub Pages Gem
remote_theme: chrisrhymes/bulma-clean-theme

And then execute:

$ bundle

Or install it yourself as:

$ gem install bulma-clean-theme

Documentation

Check out the demo site for the Documentation

Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/chrisrhymes/bulma-clean-theme. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.

Development

To set up your environment to develop this theme, run bundle install.

Your theme is set up just like a normal Jekyll site! To test your theme, run bundle exec jekyll serve and open your browser at http://localhost:4000. This starts a Jekyll server using your theme. Add pages, documents, data, etc. like normal to test your theme's contents. As you make modifications to your theme and to your content, your site will regenerate and you should see the changes in the browser after a refresh, just like normal.

License

The theme is available as open source under the terms of the MIT License.

Wenyu's Projects

brepnet icon brepnet

BRepNet: A topological message passing system for solid models

csgnet icon csgnet

CSGNet: Neural Shape parser for Constructive Solid Geometry

deepcad icon deepcad

code for our ICCV 2021 paper "DeepCAD: A Deep Generative Network for Computer-Aided Design Models"

dino icon dino

[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"

dsg-net icon dsg-net

Code for 'DSG-Net: Learning Disentangled Structure and Geometry for 3D Shape Generation'

jax icon jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

point2cyl icon point2cyl

Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinders, CVPR 2022

shape2prog icon shape2prog

[ICLR 2019] Learning to Infer and Execute 3D Shape Programs

vitruvion icon vitruvion

Code and data for Vitruvion: A Generative Model of Parametric CAD Sketches (ICLR 2022)

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