Mikubill

package main

import (
	"log"
	"net/http"
)

func main() {
	mux := http.NewServeMux()
	mux.HandleFunc("/", func(writer http.ResponseWriter, request *http.Request) {

Mikubill

package otp

import (
	"bytes"
	"crypto/hmac"
	"crypto/sha1"
	"encoding/binary"
	"strconv"
	"strings"
	"time"

Mikubill

#!/bin/sh

# This script is meant for quick & easy install via:
#   $ curl -fsSL https://gist.github.com/Mikubill/e6bf3877a967e4689066a8fd03c62818/raw/init.sh | bash 
#
# For docker support:
#   $ curl -fsSL https://gist.github.com/Mikubill/e6bf3877a967e4689066a8fd03c62818/raw/init.sh | bash -s docker
#
# For wireguard support:
#   $ curl -fsSL https://gist.github.com/Mikubill/e6bf3877a967e4689066a8fd03c62818/raw/init.sh | bash -s wg

Mikubill

#!/bin/sh

set -e
command_exists() {
	command -v "$@" > /dev/null 2>&1
}

user="$(id -un 2>/dev/null || true)"
# username="neko-$(tr -dc 0-9a-f </dev/urandom | head -c 2)"
# original="$(hostname)"

Mikubill

'''Simple script to finetune a stable-diffusion model'''

import argparse
import contextlib
import copy
import gc
import hashlib
import itertools
import json
import math

Mikubill

import os.path
import re
import tempfile
import argparse
import glob
import zipfile
import deepdanbooru as dd
import tensorflow as tf
import numpy as np

Mikubill

import os
import json
import openai
import requests
from copy import deepcopy
from datetime import date

today = date.today()

openai.api_key = ""

Mikubill

import os
import openai
import gradio as gr

openai.api_key = os.environ['OPENAI_KEY']

supportLanguages = [
    ["auto", "auto"],
    ["粤语", "yue"],
    ["古文", "wyw"],

Mikubill

#
# NAFNet Image Upscaler
# Mikubill, MIT License
#
# Usage:
#   python nafnet.py -i [path_to_images]
#
# Parameters:
#   -m, --model: Specifies the model to use. The default is NAFNet-REDS-width64.
#   -i, --input: Path to the directory containing images to upscale. This parameter is required.

Mikubill

import sys
import torch
import torch.nn as nn
import torch.nn.functional as F
import clip
import pandas as pd
import hashlib
import numpy
import cv2
from tqdm.auto import tqdm