| """ | |
| The most atomic way to train and inference 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 |
| // ==UserScript== | |
| // @name Remove Instagram Unfollowed Content | |
| // @version 2024-03-02 | |
| // @author Jin-Cheng Guu | |
| // @match https://www.instagram.com/* | |
| // @description Remove unfollowed content from the instagram main page. | |
| // ==/UserScript== | |
| (function() { |
| rule Paragon_Spyware_IOCs | |
| { | |
| meta: | |
| description = "Indicators of compromise (IOCs) for Paragon Solutions Graphite spyware from the Citizen Lab report 'Virtue or Vice? A First Look at Paragon’s Proliferating Spyware Operations'" | |
| author = "ChatGPT" | |
| date = "2025-03-29" | |
| reference = "https://citizenlab.ca/2025/03/a-first-look-at-paragons-proliferating-spyware-operations/" | |
| strings: | |
| // Suspected customer domains (Table 4) |
| import tiktoken | |
| import langdetect | |
| T = tiktoken.get_encoding("o200k_base") | |
| length_dict = {} | |
| for i in range(T.n_vocab): | |
| try: | |
| length_dict[i] = len(T.decode([i])) | |
| except: |
Fetches daily Twilio usage data into a Google Sheets spreadsheet.
