karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

peyanski

esphome:
  name: ld2410-esp32
  friendly_name: ld2410-esp32

esp32:
  board: esp32dev
  framework:
    type: arduino

# Enable logging

npearce

UPDATE (March 2020, thanks @ic): I don't know the exact AMI version but yum install docker now works on the latest Amazon Linux 2. The instructions below may still be relevant depending on the vintage AMI you are using.

Amazon changed the install in Linux 2. One no-longer using 'yum' See: https://aws.amazon.com/amazon-linux-2/release-notes/

Docker CE Install

sudo amazon-linux-extras install docker
sudo service docker start

nadavrot

High-Performance Matrix Multiplication

This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).

Intro

Matrix multiplication is a mathematical operation that defines the product of

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

vitorgalvao

-- AppleScript --

-- This example is meant as a simple starting point to show how to get the information in the simplest available way.
-- Keep in mind that when asking for a `return` after another, only the first one will be output.
-- This method is as good as its JXA counterpart.

-- Webkit variants include "Safari", "Webkit", "Orion".
-- Specific editions are valid, including "Safari Technology Preview".
-- "Safari" Example:
tell application "Safari" to return name of front document

KdotJPG

/**
 * K.jpg's OpenSimplex 2, smooth variant ("SuperSimplex")
 *
 * More language ports, as well as legacy 2014 OpenSimplex, can be found here:
 * https://github.com/KdotJPG/OpenSimplex2
 */

public class OpenSimplex2S {

    private static final long PRIME_X = 0x5205402B9270C86FL;

lucascaton

brew remove mysql

brew cleanup

launchctl unload -w ~/Library/LaunchAgents/com.mysql.mysqld.plist

rm ~/Library/LaunchAgents/com.mysql.mysqld.plist

sudo rm -rf /usr/local/var/mysql

mrdwab

stratified <- function(df, group, size, select = NULL, 
                       replace = FALSE, bothSets = FALSE) {
  if (is.null(select)) {
    df <- df
  } else {
    if (is.null(names(select))) stop("'select' must be a named list")
    if (!all(names(select) %in% names(df)))
      stop("Please verify your 'select' argument")
    temp <- sapply(names(select),
                   function(x) df[[x]] %in% select[[x]])

jookyboi

Libraries

• 960 Grid System - An effort to streamline web development workflow by providing commonly used dimensions, based on a width of 960 pixels. There are two variants: 12 and 16 columns, which can be used separately or in tandem.
• Compass - Open source CSS Authoring Framework.
• Bootstrap - Sleek, intuitive, and powerful mobile first front-end framework for faster and easier web development.
• Font Awesome - The iconic font designed for Bootstrap.
• Zurb Foundation - Framework for writing responsive web sites.
• SASS - CSS extension language which allows variables, mixins and rules nesting.
• Skeleton - Boilerplate for responsive, mobile-friendly development.

Guides