JupyterLite demo deployed to GitHub Pages 🚀

Related tags

Deep Learningdemo
Overview

JupyterLite Demo

lite-badge

JupyterLite deployed as a static site to GitHub Pages, for demo purposes.

Try it in your browser

➡️ https://jupyterlite.github.io/demo

github-pages

Requirements

JupyterLite is being tested against modern web browsers:

  • Firefox 90+
  • Chromium 89+

Usage

This repository provides a demonstration of how to:

  • build a JupyterLite release using prebuilt JupyterLite assets that bundles a collection of pre-existing Jupyter notebooks as part of the distribution;
  • deploy the release to GitHub Pages.

The process is automated using Github Actions.

You can use this repository in two main ways:

  • generate a new repository from this template repository and build and deploy your own site to the corresponding Github Pages site;
  • build a release from a PR made to this repository and download the release from the created GitHub Actions artifact.

Using Your Own Repository to Build a Release and Deploy it to Github Pages

Requires Github account.

Click on "Use this template" to generate a repository of your own from this template:

template

From the Actions tab on your repository, ensure that workflows are enabled. When you make a commit to the main branch, a Github Action will run to build your JupoyterLite release and deploy it to the repository's Github Pages site. By default, the Github Pages site will be found at YOUR_GITHUB_USERNAME.github.io/YOUR_REPOSITORY-NAME. You can also check the URL from the Repository Settings tab Pages menu item.

If the deployment failed, go to "Settings - Actions - General", in the "Workflow permissions" section, check "Read and write permissions". Update files such as readme, and commit so that GitHub rebuids and re-deploys the project. Go to "Settings - Pages", choose "gh-pages" as the source.

Add any additional requirements as required to the requirements.txt file.

You can do this via the Github website by selecting the requirements.txt file, clicking to edit it, making the required changes then saving ("committing") the result to the main branch of your repository.

Modify the contents of the contents folder to include the notebooks you want to distribute as part of your distribution.

You can do this by clicking on the contents directory and dragging notebooks from your desktop onto the contents listing. Wait for the files to be uploaded and then save them ("commit" them) to the main branch of the repository.

Check that you have Github Pages enabled for your repository: from your repository Settings tab, select the Pages menu item and ensure that the source is set to gh-pages.

When you commit a file, an updated release will be built and published on the Github Pages site. Note that it may take a few minutes for the Github Pages site to be updated. Do a hard refresh on your Github Pages site in your web browser to see the new release.

Further Information and Updates

For more info, keep an eye on the JupyterLite documentation:

Deploy a new version of JupyterLite

To change the version of the prebuilt JupyterLite assets, update the jupyterlite package version in the requirements.txt file.

The requirements.txt file can also be used to add extra prebuilt ("federated") JupyterLab extensions to the deployed JupyterLite website.

Commit and push any changes. The site will be deployed on the next push to the main branch.

Development

Create a new environment:

mamba create -n jupyterlite-demo
conda activate jupyterlite-demo
pip install -r requirements.txt

Then follow the steps documented in the Configuring section.

Owner
JupyterLite
Wasm powered Jupyter running in the browser 💡
JupyterLite
Connecting Java/ImgLib2 + Python/NumPy

imglyb imglyb aims at connecting two worlds that have been seperated for too long: Python with numpy Java with ImgLib2 imglyb uses jpype to access num

ImgLib2 29 Dec 21, 2022
Feature board for ERPNext

ERPNext Feature Board Feature board for ERPNext Development Prerequisites k3d kubectl helm bench Install K3d Cluster # export K3D_FIX_CGROUPV2=1 # use

Revant Nandgaonkar 16 Nov 09, 2022
The official repository for Deep Image Matting with Flexible Guidance Input

FGI-Matting The official repository for Deep Image Matting with Flexible Guidance Input. Paper: https://arxiv.org/abs/2110.10898 Requirements easydict

Hang Cheng 51 Nov 10, 2022
Implement slightly different caffe-segnet in tensorflow

Tensorflow-SegNet Implement slightly different (see below for detail) SegNet in tensorflow, successfully trained segnet-basic in CamVid dataset. Due t

Tseng Kuan Lun 364 Oct 27, 2022
Coursera - Quiz & Assignment of Coursera

Coursera Assignments This repository is aimed to help Coursera learners who have difficulties in their learning process. The quiz and programming home

浅梦 828 Jan 04, 2023
Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)

DQC: Differentiable Quantum Chemistry Differentiable quantum chemistry package. Currently only support differentiable density functional theory (DFT)

75 Dec 02, 2022
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

Hui Wu 19 Oct 21, 2022
A sample pytorch Implementation of ACL 2021 research paper "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Span-ASTE-Pytorch This repository is a pytorch version that implements Ali's ACL 2021 research paper Learning Span-Level Interactions for Aspect Senti

来自丹麦的天籁 10 Dec 06, 2022
Transformer in Computer Vision

Transformer-in-Vision A paper list of some recent Transformer-based CV works. If you find some ignored papers, please open issues or pull requests. **

506 Dec 26, 2022
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M

Kevin Lu 1.4k Jan 07, 2023
Vector Quantization, in Pytorch

Vector Quantization - Pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a

Phil Wang 665 Jan 08, 2023
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

YITUTech 1k Dec 31, 2022
An NVDA add-on to split screen reader and audio from other programs to different sound channels

An NVDA add-on to split screen reader and audio from other programs to different sound channels (add-on idea credit: Tony Malykh)

Joseph Lee 7 Dec 25, 2022
Bald-to-Hairy Translation Using CycleGAN

GANiry: Bald-to-Hairy Translation Using CycleGAN Official PyTorch implementation of GANiry. GANiry: Bald-to-Hairy Translation Using CycleGAN, Fidan Sa

Fidan Samet 10 Oct 27, 2022
[ICCV 2021] Deep Hough Voting for Robust Global Registration

Deep Hough Voting for Robust Global Registration, ICCV, 2021 Project Page | Paper | Video Deep Hough Voting for Robust Global Registration Junha Lee1,

Junha Lee 10 Dec 02, 2022
An updated version of virtual model making

Model-Swap-Face v2   这个项目是基于stylegan2 pSp制作的,比v1版本Model-Swap-Face在推理速度和图像质量上有一定提升。主要的功能是将虚拟模特进行环球不同区域的风格转换,目前转换器提供西欧模特、东亚模特和北非模特三种主流的风格样式,可帮我们实现生产资料零成

seeprettyface.com 62 Dec 09, 2022
Codebase for the paper titled "Continual learning with local module selection"

This repository contains the codebase for the paper Continual Learning via Local Module Composition. Setting up the environemnt Create a new conda env

Oleksiy Ostapenko 20 Dec 10, 2022
Official PyTorch implementation of "ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows"

ArtFlow Official PyTorch implementation of the paper: ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows Jie An*, Siyu Huang*, Yibing

123 Dec 27, 2022
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network

Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network The performances of tree ensemb

Mustapha Unubi Momoh 2 Sep 13, 2022
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution

Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a

Oliver Hahn 16 Dec 23, 2022