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

fofr

name	govuk-style
description	Write and edit in GOV.UK / GDS house style — plain English, active voice, front-loaded content, sentence case, and no bold or italics for emphasis. Use when writing or editing reports, research write-ups, guidance, documentation, summaries, or any prose where clarity and accessibility matter.
user-invokable	true
args	name description required target The document or text to write or rewrite in GOV.UK style (optional) false

salihkinali

<?php
session_start();
ob_start();
session_destroy();
echo "<center>Cikis Yaptiniz. Ana Sayfaya Yonlendiriliyorsunuz.</center>";
header("Refresh: 1; url=../index.php");
ob_end_flush();
?>

mmozeiko

This downloads standalone MSVC compiler, linker & other tools, also headers/libraries from Windows SDK into portable folder, without installing Visual Studio. Has bare minimum components - no UWP/Store/WindowsRT stuff, just files & tools for native desktop app development.

Run py.exe portable-msvc.py and it will download output into msvc folder. By default it will download latest available MSVC & Windows SDK from newest Visual Studio.

You can list available versions with py.exe portable-msvc.py --show-versions and then pass versions you want with --msvc-version and --sdk-version arguments.

To use cl.exe/link.exe first run setup_TARGET.bat - after that PATH/INCLUDE/LIB env variables will be updated to use all the tools as usual. You can also use clang-cl.exe with these includes & libraries.

To use clang-cl.exe without running setup.bat, pass extra /winsysroot msvc argument (msvc is folder name where output is stored).

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.

eenblam

Linux Networking Reading List

Currently in no particular order. Most of these are kind of ancient.

Where's all the modern documentation? So much of what I've turned up searching is other folks complaining about having few options beyond reading source code.

The OREILLY books, while dated, seem to be some of the best available. Note that these can be read with a 7-day trial. Do this! At least get through the introduction section and first chapter of each to see if it's what you're after.

https://www.netfilter.org/

reinaldocoelho

# Movido para projeto pessoal Chezmoi na pasta ~/.myscripts/install_ubuntu.sh

JulioBorges

1. Código para mergear os cookies:

const oldCookieString = $('data').first().json.cookie || "";
const setCookieArray = $("get-setcookies").first().json.headers['set-cookie'] || [];

let cookieMap = {};

if (oldCookieString) {
    oldCookieString.split(';').forEach(c => {

tandpfun

name

extract-clothing-cutouts

description

Extract high-quality, deduplicated transparent ecommerce clothing cutouts from a folder of photographs where people wear one or more garments. Use when Codex must find outfit or model photos, identify unique clothing across images, create focused references, reconstruct complete garments with Imagegen, remove a solid chroma background into RGBA PNGs, and output only the finished clothing images into a new folder under the current working directory.

Extract Clothing Cutouts

Turn photographs of worn clothing into source-faithful standalone catalog PNGs. Treat each result as a reconstruction from visible evidence, not literal segmentation whenever the wearer or another layer occludes part of the garment.

Start by asking for two paths