msurguy

Other people's projects:

• https://github.com/laracasts/URL-Shortener URL Shortener by Jeffrey Way
• https://github.com/basco-johnkevin/laravelsnippets Source code of http://laravelsnippets.com website
• https://github.com/jesseterry/FusionInvoice FusionInvoice is built for freelancers and small businesses who need a simple, yet powerful self-hosted web based invoicing system.
• https://github.com/ezynda3/burnmsg is a self-destructing encrypted message app. A demo is also running on https://burnmsg.com
• https://github.com/martindilling/auto-generating-gallery the demo is at http://gallerydemo.martindilling.com/

My projects (tutorials are on my blog at http://maxoffsky.com):

• https://github.com/CodepadME/laravel-tricks - Source of Laravel-tricks.com

addyosmani

CSS Layout Debugger

A tweet-sized debugger for visualizing your CSS layouts. Outlines every DOM element on your page a random (valid) CSS hex color.

One-line version to paste in your DevTools

Use $$ if your browser aliases it:

~ 108 byte version

thiloplanz

Zero knowledge databases

The idea

The idea is to provide a database as a service to end users in such a way that no one except the user herself can access the data, not even the hosting provider or the database administrator.

Advantages

• A privacy- and/or security-conscious user will have more trust in such a setup.
• The service provider cannot be coerced to release the data they were trusted with, and he cannot be held responsible for the content he is storing.

numanturle

import time
import frida
import json
enc_cipher_hashcodes = [] #cipher objects with Cipher.ENCRYPT_MODE will be stored here
dec_cipher_hashcodes = [] #cipher objects with Cipher.ENCRYPT_MODE will be stored here


def my_message_handler(message, payload):
    #mainly printing the data sent from the js code, and managing the cipher objects according to their operation mode
    if message["type"] == "send":

rain-1

This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

• Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.