Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.
Avoid being a link dump. Try to provide only valuable well tuned information.
Neural network links before starting with transformers.
# Stop all containers | |
docker stop `docker ps -qa` | |
# Remove all containers | |
docker rm `docker ps -qa` | |
# Remove all images | |
docker rmi -f `docker images -qa ` | |
# Remove all volumes |
Typing vagrant
from the command line will display a list of all available commands.
Be sure that you are in the same directory as the Vagrantfile when running these commands!
vagrant init
-- Initialize Vagrant with a Vagrantfile and ./.vagrant directory, using no specified base image. Before you can do vagrant up, you'll need to specify a base image in the Vagrantfile.vagrant init <boxpath>
-- Initialize Vagrant with a specific box. To find a box, go to the public Vagrant box catalog. When you find one you like, just replace it's name with boxpath. For example, vagrant init ubuntu/trusty64
.vagrant up
-- starts vagrant environment (also provisions only on the FIRST vagrant up)(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
int xPos = (canvas.getWidth() / 2); | |
int yPos = (int) ((canvas.getHeight() / 2) - ((textPaint.descent() + textPaint.ascent()) / 2)) ; | |
//((textPaint.descent() + textPaint.ascent()) / 2) is the distance from the baseline to the center. | |
canvas.drawText("Hello", xPos, yPos, textPaint); |
Using gem aws-sdk for a ror application for uploading images to s3 | |
Uploading images to a fixed bucket with different folders for each object or application. | |
The s3 keeps a limitation on the number of buckets creattion whereas there is no | |
limitation for content inside a bucket. | |
This code will upload image for a user to s3 using aws-sdk gem. The bucket and the image uploaded are made public | |
so that the images uploaded are directly accessible. The input it takes is the image complete path | |
where it is present, folder in which it should be uploaded and user_id for whom it should | |
be uploaded. |
// SymSpell: 1000x faster through Symmetric Delete spelling correction algorithm | |
// | |
// The Symmetric Delete spelling correction algorithm reduces the complexity of edit candidate generation and dictionary lookup | |
// for a given Damerau-Levenshtein distance. It is three orders of magnitude faster and language independent. | |
// Opposite to other algorithms only deletes are required, no transposes + replaces + inserts. | |
// Transposes + replaces + inserts of the input term are transformed into deletes of the dictionary term. | |
// Replaces and inserts are expensive and language dependent: e.g. Chinese has 70,000 Unicode Han characters! | |
// | |
// Copyright (C) 2012 Wolf Garbe, FAROO Limited | |
// Version: 1.6 |