Treelar ninjawarrior1337

Twitter API Keys

Twitter for iPhone

Consumer key: IQKbtAYlXLripLGPWd0HUA
Consumer secret: GgDYlkSvaPxGxC4X8liwpUoqKwwr3lCADbz8A7ADU

Twitter for Android

Consumer key: 3nVuSoBZnx6U4vzUxf5w
Consumer secret: Bcs59EFbbsdF6Sl9Ng71smgStWEGwXXKSjYvPVt7qys

Twitter for Google TV

Consumer key: iAtYJ4HpUVfIUoNnif1DA

LVM cache in Fedora

From the man-pages: "The cache logical volume type uses a small and fast LV to improve the performance of a large and slow LV. It does this by storing the frequently used blocks on the faster LV. LVM refers to the small fast LV as a cache pool LV. The large slow LV is called the origin LV. Due to requirements from dm-cache (the kernel driver), LVM further splits the cache pool LV into two devices - the cache data LV and cache metadata LV. The cache data LV is where copies of data blocks are kept from the origin LV to increase speed. The cache metadata LV holds the accounting information that specifies where data blocks are stored (e.g. on the origin LV or on the cache data LV). Users should be familiar with these LVs if they wish to create the best and most robust cached logical volumes. All of these associated LVs must be in the same VG."

Assuming LVM is already setup in HDD (e.g. from anaconda) and SSD is untouched.

Create a physical

	"""
	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

	# MINIMAL USB gadget setup using CONFIGFS for simulating Razer Gaming HID
	# devices for triggering the vulnerable Windows Driver installer
	# credits for the Windows Driver install vuln: @j0nh4t
	#
	# https://twitter.com/j0nh4t/status/1429049506021138437
	# https://twitter.com/an0n_r0/status/1429263450748895236
	#

	# the script was developed & tested on Android LineageOS 18.1