rise-worlds

for 4.2.4 or higher, 4.2.5,4.2.6,4.3.7, it's works, this is the way which makes Always in evaluation mode.

1. open Terminal, go to the dir : cd /Applications/Beyond Compare.app/Contents/MacOS
2. change the name BCompare to BCompare.bak: mv BCompare BCompare.bak
3. touch a file name BCompare , and chmod a+ux BCompare : touch BCompare && chmod a+ux BCompare
4. open BCompare with text editor, insert the script :

#!/bin/bash
rm "/Users/$(whoami)/Library/Application Support/Beyond Compare/registry.dat"
"`dirname "$0"`"/BCompare.bak $@

karpathy

"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

k16shikano

name	japanese-tech-writing
description	日本語の技術文書・書籍原稿の文章規範。整形（一文一行、引用ブロック、脚注、コラム記法）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

日本語技術文書の文章規範

日本語で技術的な原稿（書籍の章、記事、解説文）を書く・推敲するときは、以下の規範に従う。

整形

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

mhmdiaa

import requests
import re
import sys
from multiprocessing.dummy import Pool


def robots(host):
    r = requests.get(
        'https://web.archive.org/cdx/search/cdx\
        ?url=%s/robots.txt&output=json&fl=timestamp,original&filter=statuscode:200&collapse=digest' % host)

mzahidriaz

class ContactFinder {
  #db;
  #chatToFind;
  #dbName = "model-storage";
  #chatsCol = "chat";
  #contactCol = "contact";
  #groupCol = "participant";

  constructor(chatGroupName) {
    this.#chatToFind = chatGroupName;

bradtraversy

MySQL Cheat Sheet

Help with SQL commands to interact with a MySQL database

MySQL Locations

• Mac /usr/local/mysql/bin
• Windows /Program Files/MySQL/MySQL version/bin
• Xampp /xampp/mysql/bin

Add mysql to your PATH

coverband

# ---------------------------------------------
# This is a small python utility that will get a list of all blackbox.ai models that are supposed to be accessible to you, 
# and do a quick test call with each to figure out which ones ACTUALLY work. Many models are listed by blackbox.ai, but unfortunately 
# a large number of them are not actually accessible, some due to API rate throttling by the provider, some due to the provider asking 
# you to accept their terms/policies before granting access, and some due to incorrect path/documentation/version by blackbox.ai .
# ---------------------------------------------

import requests
import json
import time

ErikFontanel

#!/bin/sh
# This script will fetch the Googlevideo ad domains and append them to the Pi-hole block list.
# Run this script daily with a cron job (don't forget to chmod +x)
# More info here: https://discourse.pi-hole.net/t/how-do-i-block-ads-on-youtube/253/136

# File to store the YT ad domains
FILE=/etc/pihole/youtube.hosts

# Fetch the list of domains, remove the ip's and save them
curl 'https://api.hackertarget.com/hostsearch/?q=googlevideo.com' \