hizkifw

#!/bin/sh

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

do_install() {
        set -e
        
        user="$(id -un 2>/dev/null || true)"

hizkifw

#!/usr/bin/env bash

set -euo pipefail

model_name="$1"

if [[ -z "$model_name" ]]; then
    echo "Usage: $0 <model_name>"
    exit 1
fi

hizkifw

#!/usr/bin/env bash

python -m venv venv
. ./venv/bin/activate
python -m pip install jupyter jupyterlab ipywidgets notebook numpy pandas scipy matplotlib Pillow seaborn tqdm
python -m jupyter lab

hizkifw

apiVersion: v1
kind: Config
clusters:
- name: dummy
  cluster:
    api-version: v1
    server: http://example.com
contexts:
- name: dummy
  context:

hizkifw

<#
.SYNOPSIS
    Prune and compact the Docker VHDX disk file
#>

# Check if running as administrator
$CurrentUser = New-Object Security.Principal.WindowsPrincipal `
    $([Security.Principal.WindowsIdentity]::GetCurrent())
if (-not $CurrentUser.IsInRole([Security.Principal.WindowsBuiltInRole]::Administrator)) {
    # Restart as administrator

hizkifw

How to mount cephfs

1. Create authorization

   root@cephhost:~# ceph fs authorize cephfs client.clientname /some/path rw
   [client.clientname]
           key = ...............
   

Save it in the machine where you wanna mount, at /etc/ceph/ceph.client.clientname.keyring

hizkifw

--- json.hpp    2023-01-09 15:13:04.871631532 +0800
+++ json2.hpp   2023-01-09 15:13:24.414084972 +0800
@@ -6054,7 +6054,7 @@
             {
                 case value_t::array:
                 {
-                    return *lhs.m_value.array < *rhs.m_value.array;
+                    return (*lhs.m_value.array) < (*rhs.m_value.array);
                 }
                 case value_t::object:

hizkifw

# Options to pass to earlyoom
# /etc/default/earlyoom
EARLYOOM_ARGS="-r 3600 -n --avoid '(^|/)(init|systemd|Xorg|sshd|pipewire(-pulse)?|dunst|nitrogen|polybar|NetworkManager|dbus-daemon|xss-lock|nm-applet)$' --prefer '(^|/)(Discord|thunderbird|rust-analyzer|lens|telegram-desktop|firefox|chromium)$'"

hizkifw

"""
clipbooru.py

Go through a list of (md5).(ext), downloads them from danbooru, and compute CLIP
embeddings. Images are downloaded in parallel while inference is being done, so
this should run as fast as your hardware/network can handle.
"""

# requirements.txt
"""

hizkifw

<#
.SYNPOSIS
  Download all danbooru pages
#>

Param(
  [string]$DanbooruURL = "https://danbooru.donmai.us/"
)

$DanbooruURL = $DanbooruURL.TrimEnd("/")