Fadi002

import sys
import os

NOP = 0x90
offsets_and_values = {
    0x00030170: 0x00,
    0x000A94D0: NOP, 0x000A94D1: NOP, 0x000A94D2: NOP, 0x000A94D3: NOP, 0x000A94D4: NOP, 0x000A94D5: NOP, 0x000A94D6: NOP, 0x000A94D7: NOP, 0x000A94D8: NOP, 0x000A94D9: NOP, 0x000A94DA: NOP, 0x000A94DB: NOP, 0x000A94DC: NOP, 0x000A94DD: NOP, 0x000A94DE: NOP, 0x000A94DF: NOP, 0x000A94E0: NOP, 0x000A94E1: NOP, 0x000A94E2: NOP, 0x000A94E3: NOP, 0x000A94E4: NOP, 0x000A94E5: NOP, 0x000A94E6: NOP, 0x000A94E7: NOP, 0x000A94E8: NOP, 0x000A94E9: NOP, 0x000A94EA: NOP, 0x000A94EB: NOP, 0x000A94EC: NOP, 0x000A94ED: NOP, 0x000A94EE: NOP, 0x000A94EF: NOP, 0x000A94F0: NOP, 0x000A94F1: NOP, 0x000A94F2: NOP, 0x000A94F3: NOP, 0x000A94F4: NOP, 0x000A94F5: NOP, 0x000A94F6: NOP, 0x000A94F7: NOP, 0x000A94F8: NOP, 0x000A94F9: NOP, 0x000A94FA: NOP, 0x000A94FB: NOP, 0x000A94FC: NOP, 0x000A94FD: NOP, 0x000A94FE: NOP, 0x000A94FF: NOP, 0x000A9500: NOP, 0x000A9501: NOP, 0x000A9502: NOP, 0x000A9503: NOP, 0x000A9504: NOP, 0x000A9505: NOP, 0x000A9506: NO

YewFence

// ==UserScript==
// @name         批改网解除禁止粘贴
// @namespace    https://yewfence.github.io
// @version      1.0.0
// @description  解除批改网写作页的粘贴/右键/选择/拖拽限制（老师在作文要求里开了"禁止粘贴"时用）
// @author       YewFence
// @match        https://www.pigai.org/*
// @run-at       document-start
// @grant        none
// ==/UserScript==

xiety

#! "net9.0"
#r "nuget: OpenCvSharp4, 4.10.0.20241108"
#r "nuget: OpenCvSharp4.runtime.win, 4.10.0.20241108"
#r "nuget: SixLabors.ImageSharp, 3.1.6"
#r "nuget: FFMpegCore, 5.1.0"
#r "nuget: System.Text.Json, 9.0.0"

#nullable enable

using System.Runtime.InteropServices;

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.

acapola

#include <stdint.h>     //for int8_t
#include <string.h>     //for memcmp
#include <wmmintrin.h>  //for intrinsics for AES-NI
//compile using gcc and following arguments: -g;-O0;-Wall;-msse2;-msse;-march=native;-maes

//internal stuff

//macros
#define DO_ENC_BLOCK(m,k) \
	do{\

embedding-shapes

# Place in /etc/systemd/system/var-mnt-nas.mount
# Run `sudo systemctl daemon-reload` then:
# `sudo systemctl enable --now var-mnt-nas.mount`
# Replace "/tank/data" with your remote location
# Replace "/var/mnt/nas" where you want to mount it locally
# Replace "20.0.0.1" with the IP you use for the NAS/networked storage
[Unit]
Description=NAS data

[Mount]

supersonictw

#!/bin/bash
# Ollama Model Export Script
# Usage: bash ollama-export.sh vicuna:7b
# SPDX-License-Identifier: MIT (https://ncurl.xyz/s/o_o6DVqIR)
# https://gist.github.com/supersonictw/f6cf5e599377132fe5e180b3d495c553

# Interrupt if any error occurred
set -e

# Declare

kellydavid

Set up Yubikey (5C NFC) for SSH authentication

• yubikey 5C NFC
• macOS Monterey 12.2.1

For in depth details on how to set up a Yubikey for SSH on a mac, check out the following:

• https://florin.myip.org/blog/easy-multifactor-authentication-ssh-using-yubikey-neo-tokens
• https://gist.github.com/ixdy/6fdd1ecea5d17479a6b4dab4fe1c17eb

mathix420

// ==UserScript==
// @name        Freedium Article Redirect
// @namespace   Violentmonkey Scripts
// @run-at      document-start
// @match       *://medium.com/*
// @match       *://*.medium.com/*
// @match       *://nytimes.com/*
// @match       *://*.nytimes.com/*
// @match       *://washingtonpost.com/*
// @match       *://*.washingtonpost.com/*

demnbrooo

극장판 치이카와: 인어 섬의 비밀 (.2026.) 다시;보기 스트리밍 정보

⭐극장판 치이카와: 인어 섬의 비밀 무료;보기 전체;보기 무료로 시청 공식 홈페이지 VOD 및 티빙(TVING), 웨이브(Wavve)에서 다시 보기가 가능합니다.

이 페이지에서는 극장판 치이카와: 인어 섬의 비밀 의 기본 영화 정보와 개봉 관련 내용, 장르, 출연진, 작품 특징 및 향후 공개와 관련해 확인할 수 있는 정보를 정리했습니다.

➡️ 극장판 치이카와: 인어 섬의 비밀 최신 영화 정보 보기