HuggingFace Page for model download: https://huggingface.co/hakurei/waifu-diffusion-v1-3
| lemmy_communities_url = "https://browse.feddit.de/communities.json?nocache=" | |
| import json, urllib.request, time, sys, os | |
| print("H3's Reddit to Lemmy script v0.4.1") | |
| savefile_name = "" | |
| use_savefile = 0 | |
| savefile_data = {} |
| # Script for converting a HF Diffusers saved pipeline to a Stable Diffusion checkpoint. | |
| # *Only* converts the UNet, VAE, and Text Encoder. | |
| # Does not convert optimizer state or any other thing. | |
| # Written by jachiam | |
| import argparse | |
| import os.path as osp | |
| import torch |
In the configuration pictured below, multiple identically-configured Adafruit CircuitPython 8.0.0-beta.0 on 2022-08-18; Adafruit QT Py ESP32S2 with ESP32S2 are used to create a Redundant Array of mDNS http Servers. The devices could be physically together or scattered around, as long as they are on the same LAN. Once configured, no USB connection is necessary for operation.
Each is running CircuitPython 8 Web Workflow: https://docs.circuitpython.org/en/latest/docs/workflows.html#web
Web Workflow automatically connects to a Wi-Fi Access Point based on credentials in a /.env file in the root of the CIRCUITPY drive filesystem, and creates an HTTP Server (port can be changed with CIRCUITPY_WEB_API_PORT= in the /.env file; it's port 80 by default).
In code.py, run an HTTP Server using (for example):
https://docs.circuitpython.org/projects/httpserver/en/latest/api.html
Make sure that the ports are different between the Web Workflow HTTP Server and the code.py HTTP Server (e.g., set
| import network | |
| import socket | |
| import time | |
| from machine import Pin | |
| import uasyncio as asyncio | |
| led = Pin(15, Pin.OUT) | |
| onboard = Pin("LED", Pin.OUT, value=0) |
| import sys | |
| from flask import Flask, request, make_response, send_file | |
| from flask_restful import Resource, Api | |
| app = Flask(__name__) | |
| api = Api(app) | |
| class TiddlyWiki(Resource): |
Below are table of various projects that can completely exhaust n-bits of keyspace. In other words, counting completely and fully from 0 to 2ⁿ-1.
This Gist implies no discussion about how this is relevant to quantum computing using Grover's algorithm, meet-in-the-middle or birthday attacks, or anything of the like. It's strictly a Gist about raw speed, measuring the result in bits.
If you know of other noteworthy and verifiable brute force searching projects,
Simple guide for setting up OTG modes on the Raspberry Pi Zero - By Andrew Mulholland (gbaman).
The Raspberry Pi Zero (and model A and A+) support USB On The Go, given the processor is connected directly to the USB port, unlike on the B, B+ or Pi 2 B, which goes via a USB hub.
Because of this, if setup to, the Pi can act as a USB slave instead, providing virtual serial (a terminal), virtual ethernet, virtual mass storage device (pendrive) or even other virtual devices like HID, MIDI, or act as a virtual webcam!
It is important to note that, although the model A and A+ can support being a USB slave, they are missing the ID pin (is tied to ground internally) so are unable to dynamically switch between USB master/slave mode. As such, they default to USB master mode. There is no easy way to change this right now.
It is also important to note, that a USB to UART serial adapter is not needed for any of these guides, as may be documented elsewhere across the int
| #!/usr/bin/python | |
| from __future__ import print_function | |
| import base64 | |
| import commands | |
| import json | |
| import sys | |
| import uuid | |
| import xmltodict |
| #!/usr/bin/python3 | |
| # | |
| # Simple Bloom filter implementation in Python 3 | |
| # Copyright 2017 Hector Martin "marcan" <marcan@marcan.st> | |
| # Licensed under the terms of the MIT license | |
| # | |
| # Written to be used with the Have I been pwned? password list: | |
| # https://haveibeenpwned.com/passwords | |
| # | |
| # Download the pre-computed filter here (968MB, k=11, false positive p=0.0005): |