OrionReed

// 3D Dom viewer, copy-paste this into your console to visualise the DOM as a stack of solid blocks.
// You can also minify and save it as a bookmarklet (https://www.freecodecamp.org/news/what-are-bookmarklets/)
(() => {
  const SHOW_SIDES = false; // color sides of DOM nodes?
  const COLOR_SURFACE = true; // color tops of DOM nodes?
  const COLOR_RANDOM = false; // randomise color?
  const COLOR_HUE = 190; // hue in HSL (https://hslpicker.com)
  const MAX_ROTATION = 180; // set to 360 to rotate all the way round
  const THICKNESS = 20; // thickness of layers
  const DISTANCE = 10000; // ¯\\_(ツ)_/¯

drewstaylor

const CwStargate = require("@cosmjs/cosmwasm-stargate");

const RPC = process.env.RPC;
const CONTRACT = process.env.CONTRACT;

async function cwClient() {
  const cwClient = await CwStargate.SigningCosmWasmClient.connectWithSigner(RPC, null);
  return cwClient;
}

cedrickchee

4 Steps in Running LLaMA-7B on a M1 MacBook

The large language models usability

The problem with large language models is that you can’t run these locally on your laptop. Thanks to Georgi Gerganov and his llama.cpp project, it is now possible to run Meta’s LLaMA on a single computer without a dedicated GPU.

Running LLaMA

There are multiple steps involved in running LLaMA locally on a M1 Mac after downloading the model weights.

stevedylandev

const PINATA_JWT = 'Bearer YOUR_JWT_HERE'
const PIN_QUERY = `https://api.pinata.cloud/data/pinList?status=pinned&pageLimit=1000&includeCount=false`
const fetch = require('node-fetch')

const wait = (milliseconds) => {
  return new Promise((resolve) => {
    setTimeout(resolve, milliseconds);
  });
};

syphh

def is_valid(grid, r, c, k):
    not_in_row = k not in grid[r]
    not_in_column = k not in [grid[i][c] for i in range(9)]
    not_in_box = k not in [grid[i][j] for i in range(r//3*3, r//3*3+3) for j in range(c//3*3, c//3*3+3)]
    return not_in_row and not_in_column and not_in_box


def solve(grid, r=0, c=0):
    if r == 9:
        return True

vrslev

import os

import arel
from fastapi import FastAPI, Request
from fastapi.templating import Jinja2Templates

app = FastAPI()
templates = Jinja2Templates("templates")

if _debug := os.getenv("DEBUG"):

octalmage

{
    "chainId": "phoenix-1",
    "chainName": "Terra 2.0",
    "rpc": "https://terra-rpc.polkachu.com/",
    "rest": "https://phoenix-lcd.terra.dev/",
    "stakeCurrency": {
        "coinDenom": "LUNA",
        "coinMinimalDenom": "uluna",
        "coinDecimals": 6,
        "coinGeckoId": "terra-luna"

qin-yu

Ubuntu20.04 Wine 6.0 微信中文显示方块/方框

如果希望在Ubuntu使用Windows版微信：

1. 安装 Wine sudo apt-get install wine
2. 先把环境改了省事：

   $ export WINEARCH=win32
   $ export WINEPREFIX=/home/qinyu/Wine/WeChat

3. 创建 Wine Bottle

mortenbh

Download and install dependencies

sudo apt install wget alien libjpeg62 libcurl4 libaudiofile1 libtinfo5 python mesa-opencl-icd xfonts-100dpi xfonts-75dpi

wget http://ftp.br.debian.org/debian/pool/main/o/openssl1.0/libssl1.0.2_1.0.2u-1~deb9u1_amd64.deb
wget https://download-ib01.fedoraproject.org/pub/fedora/linux/releases/33/Everything/x86_64/os/Packages/l/libpng15-1.5.30-11.fc33.x86_64.rpm

fakeroot alien -vc libpng15-1.5.30-11.fc33.x86_64.rpm

hendi

#[macro_use] extern crate rocket;

use std::env;

use anyhow::Result;

use rocket::State;
use rocket::http::Status;

use sqlx::{Pool, Postgres};