coolaj86

Chat GPT "DAN" (and other "Jailbreaks")

• https://chat.openai.com/
• Is ChatGPT "DAN" Real? Gonna find out [Part 1]
  (https://www.youtube.com/watch?v=-q8woRG9FrI)
• Part 2: I thought ChatGPT DAN was a hoax, but...
  (https://www.youtube.com/watch?v=rHZRrDu3A2U&lc=UgxfrxX8aK7gnCzkend4AaABAg)

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

gbaman

Setting up Pi Zero OTG - The quick way (No USB keyboard, mouse, HDMI monitor needed)

More details - http://blog.gbaman.info/?p=791

For this method, alongside your Pi Zero, MicroUSB cable and MicroSD card, only an additional computer is required, which can be running Windows (with Bonjour, iTunes or Quicktime installed), Mac OS or Linux (with Avahi Daemon installed, for example Ubuntu has it built in).
1. Flash Raspbian Jessie full or Raspbian Jessie Lite onto the SD card.
2. Once Raspbian is flashed, open up the boot partition (in Windows Explorer, Finder etc) and add to the bottom of the config.txt file dtoverlay=dwc2 on a new line, then save the file.
3. If using a recent release of Jessie (Dec 2016 onwards), then create a new file simply called ssh in the SD card as well. By default SSH i

lewtun

# This is a modified version of TRL's `SFTTrainer` example (https://github.com/huggingface/trl/blob/main/examples/scripts/sft_trainer.py), 
# adapted to run with DeepSpeed ZeRO-3 and Mistral-7B-V1.0. The settings below were run on 1 node of 8 x A100 (80GB) GPUs.
#
# Usage:
#   - Install the latest transformers & accelerate versions: `pip install -U transformers accelerate`
#   - Install deepspeed: `pip install deepspeed==0.9.5`
#   - Install TRL from main: pip install git+https://github.com/huggingface/trl.git
#   - Clone the repo: git clone github.com/huggingface/trl.git
#   - Copy this Gist into trl/examples/scripts
#   - Run from root of trl repo with: accelerate launch --config_file=examples/accelerate_configs/deepspeed_zero3.yaml --gradient_accumulation_steps 8 examples/scripts/sft_trainer.py  

austinmarton

/*
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 */

#include <arpa/inet.h>
#include <linux/if_packet.h>
#include <stdio.h>

mimoo

#ifndef __ERASE_FROM_MEMORY_H__
#define __ERASE_FROM_MEMORY_H__ 1

#define __STDC_WANT_LIB_EXT1__ 1
#include <stdlib.h>
#include <string.h>

void *erase_from_memory(void *pointer, size_t size_data, size_t size_to_remove) {
  #ifdef __STDC_LIB_EXT1__
   memset_s(pointer, size_data, 0, size_to_remove);

Vini2

import java.util.Random;

/**
 *
 * @author Vijini
 */

//Main class
public class SimpleDemoGA {

oskar456

#!/usr/bin/env python3

import subprocess
import json
import os
from pathlib import Path

import requests
from requests.compat import urljoin

ibndias

# This is a modified version of TRL's `SFTTrainer` example (https://github.com/huggingface/trl/blob/main/examples/scripts/sft_trainer.py), 
# adapted to run with DeepSpeed ZeRO-3 and Mistral-7B-V1.0. The settings below were run on 1 node of 8 x A100 (80GB) GPUs.
#
# Usage:
#   - Install the latest transformers & accelerate versions: `pip install -U transformers accelerate`
#   - Install deepspeed: `pip install deepspeed==0.9.5`
#   - Install TRL from main: pip install git+https://github.com/huggingface/trl.git
#   - Clone the repo: git clone github.com/huggingface/trl.git
#   - Copy this Gist into trl/examples/scripts
#   - Run from root of trl repo with: accelerate launch --config_file=examples/accelerate_configs/deepspeed_zero3.yaml --gradient_accumulation_steps 8 examples/scripts/sft_trainer.py  

naufalso