next-starter-jamstack's Introduction

A Next.js starter for the JAMstack

This is a boilerplate for using Next.js as a static site generator.

Usage

Getting started

To start your project, either:

Deploy to Netlify using the button above, or
Clone this repository and run:

npm install

This will take some time and will install all packages necessary to run the starter.

Development

While developing your website, use:

npm start

Then visit http://localhost:3000/ to preview your new website. The Next.js development server will automatically reload the CSS or refresh the whole page, when stylesheets or content changes.

Static build

To build a static version of the website inside the /dist folder, run:

npm run build

See package.json for all tasks.

Basic Concepts

You can read more about building sites and apps with Next.js in their documentation here:

https://nextjs.org/docs

Doing dynamic things

A few resources for doing anything you can imagine with a 100% static site/app on the JAMstack using Next.js. If you would like to add more resources please open a pull request!

Deploying to Netlify

The deploy to Netlify button above will create a new site and repo in one click. If you've created your repo manually, you can deploy to Netlify as follows:

Push your clone to your own GitHub repository.
Create a new site on Netlify and link the repository.

Now Netlify will build and deploy your site whenever you push to git.

next-starter-jamstack's People

Contributors

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next-starter-jamstack's Issues

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https://github.com/metlos/cm-bump/blob/master/Cargo.toml

Test

Add NVIDIA package repositories

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
sudo apt-get update

wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb

sudo apt install ./nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo apt-get update

Install NVIDIA driver

sudo apt-get install --no-install-recommends nvidia-driver-450

Reboot. Check that GPUs are visible using the command: nvidia-smi

wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/libnvinfer7_7.1.3-1+cuda11.0_amd64.deb
sudo apt install ./libnvinfer7_7.1.3-1+cuda11.0_amd64.deb
sudo apt-get update

Install development and runtime libraries (~4GB)

sudo apt-get install --no-install-recommends
cuda-11-0
libcudnn8=8.0.4.30-1+cuda11.0
libcudnn8-dev=8.0.4.30-1+cuda11.0

Install TensorRT. Requires that libcudnn8 is installed above.

sudo apt-get install -y --no-install-recommends libnvinfer7=7.1.3-1+cuda11.0
libnvinfer-dev=7.1.3-1+cuda11.0
libnvinfer-plugin7=7.1.3-1+cuda11.0

Hello

@frozen struct String

@Frozen struct String

Github telegram

https://github.com/tdlib/td/blob/master/SplitSource.php

Code

Load

import UIKit

// Import the module that corresponds with the Swift package’s library product MyLibrary.
import MyLibrary

class ViewController: UIViewController {

@IBOutlet var aLabel: UILabel!
@IBOutlet var aButton: UIButton!
@IBOutlet var anImageView: UIImageView!
@IBOutlet var aCustomView: CustomView!

override func viewDidLoad() {
    super.viewDidLoad()

    // Use a string that the package exposes as a property in the MyLibrary file.
    self.aLabel.text = MyLibrary.titleText
    
    // Load an image that the MyLibrary package makes available through a class method.
    if let imagePath = MyClass.exampleImagePath() {
        self.anImageView.image = UIImage(contentsOfFile: imagePath)
    }

    // Use the Swift package’s CustomView class.
    self.aCustomView = CustomView()        
}

// Show an alert by calling the package’s API.
@IBAction func showAlert(_ sender: Any) {
    MyClass.showAlertUsing(viewController: self)
}

}

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