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
Prototypical Networks for Few shot Learning in PyTorch

Prototypical Networks for Few shot Learning in PyTorch Simple alternative Implementation of Prototypical Networks for Few Shot Learning (paper, code)

Orobix 835 Jan 08, 2023
Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness

FL Analysis This repository contains the code and results for the paper "Towards Understanding Quality Challenges of the Federated Learning: A First L

3 Oct 17, 2022
StarGAN v2-Tensorflow - Simple Tensorflow implementation of StarGAN v2

Official Tensorflow implementation Open ! - Clova AI StarGAN v2 — Un-official TensorFlow Implementation [Paper] [Pytorch] : Diverse Image Synthesis f

Junho Kim 110 Jul 02, 2022
OSLO: Open Source framework for Large-scale transformer Optimization

O S L O Open Source framework for Large-scale transformer Optimization What's New: December 21, 2021 Released OSLO 1.0. What is OSLO about? OSLO is a

TUNiB 280 Nov 24, 2022
Neural Logic Inductive Learning

Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn

36 Nov 28, 2022
Multi-Stage Episodic Control for Strategic Exploration in Text Games

XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi

Princeton Natural Language Processing 9 May 24, 2022
Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.

pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D

Agnieszka Mikołajczyk 88 Nov 17, 2022
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

Tensorpack 6.2k Jan 01, 2023
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network

Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network This is the official implementation of

azad 2 Jul 09, 2022
The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte

Gowthami Somepalli 284 Dec 21, 2022
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

Semi-supervised-learning-for-medical-image-segmentation. Recently, semi-supervised image segmentation has become a hot topic in medical image computin

Healthcare Intelligence Laboratory 1.3k Jan 03, 2023
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red

Taehoon Kim 2.6k Dec 31, 2022
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020

TDANet: Text-Guided Neural Image Inpainting, MM'2020 (Oral) MM | ArXiv This repository implements the paper "Text-Guided Neural Image Inpainting" by L

LisaiZhang 75 Dec 22, 2022
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Yu Meng 60 Dec 30, 2022
Python PID Tuner - Based on a FOPDT model obtained using a Open Loop Process Reaction Curve

PythonPID_Tuner Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a rough e

6 Jan 14, 2022
Estimation of human density in a closed space using deep learning.

Siemens HOLLZOF challenge - Human Density Estimation Add project description here. Installing Dependencies: Install Python3 either system-wide, user-w

3 Aug 08, 2021
Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)

GS-WGAN This repository contains the implementation for GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators (NeurIPS

46 Nov 09, 2022
Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.

Codes-for-Algorithms Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.

Tracy (Shengmin) Tao 1 Apr 12, 2022
Library of various Few-Shot Learning frameworks for text classification

FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt

Thomas Dopierre 47 Jan 03, 2023
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet

PyTorch Image Classification Following papers are implemented using PyTorch. ResNet (1512.03385) ResNet-preact (1603.05027) WRN (1605.07146) DenseNet

1.2k Jan 04, 2023