FurkanGozukara

# tutorial video link : https://youtu.be/dYt9xJ7dnpU
# colab link : https://colab.research.google.com/drive/1xSbu-b-EwYd6GdaFPRVgvXBX_mciZ41e?usp=sharing
# repo link : https://github.com/ai-forever/Kandinsky-2
# used repo commit hash : a4354c04d5fbd48851866ef7d84ec444d3d50102

# those who getting cuda error
# pip uninstall torch
# pip3 install torch==1.13.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117

import os

python273

import os
os.environ["OPENAI_API_KEY"] = ""

from flask import Flask, Response, request
import threading
import queue

from langchain.chat_models import ChatOpenAI
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.schema import AIMessage, HumanMessage, SystemMessage

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)

joelgrus

from typing import TypeVar, Generic, Callable
from dataclasses import dataclass
from argparse import Namespace

T = TypeVar('T')
S = TypeVar('S')

@dataclass
class ListMap(Generic[S, T]):
    f: Callable[[T], S]

veekaybee

ChatGPT Resources

Context

ChatGPT appeared like an explosion on all my social media timelines in early December 2022. While I keep up with machine learning as an industry, I wasn't focused so much on this particular corner, and all the screenshots seemed like they came out of nowhere. What was this model? How did the chat prompting work? What was the context of OpenAI doing this work and collecting my prompts for training data?

I decided to do a quick investigation. Here's all the information I've found so far. I'm aggregating and synthesizing it as I go, so it's currently changing pretty frequently.

Model Architecture

wselfjes

FROM registry.visionhub.ru/models/base:v5 AS base

# ============ BEGIN User model environment ============
FROM ubuntu:18.04

RUN apt-get update && apt-get install -y libsm6 libxext6 libxrender-dev libglib2.0-0 ffmpeg zlib1g-dev libjpeg-dev
RUN apt-get install -y python3-pip 
RUN update-alternatives --install /usr/bin/python python /usr/bin/python3 1 
RUN update-alternatives --install /usr/bin/pip pip /usr/bin/pip3 1
RUN pip install -U pip

RhetTbull

""" Use Apple's Vision Framework via PyObjC to detect text in images 

To use:

python3 -m pip install pyobjc-core pyobjc-framework-Quartz pyobjc-framework-Vision wurlitzer

"""

import pathlib

dschwertfeger

import argparse
import math
import os
from multiprocessing import Pool, cpu_count

import numpy as np
import pandas as pd
import tensorflow as tf
from tqdm import tqdm

haccks

Setting up postfix on MacOS High Sierra

MacOS Sierra High comes with preinstalled postfix. Follow these steps to configure it on a local system:

1. Create a sasl_passwd file

sudo nano /etc/postfix/sasl_passwd

• Add this to the file

jerieljan

I use PlantUML a lot. It's what I use for drawing all sorts of diagrams and it's handy because of its easy markup (once you get used to it) while making things easy to maintain as projects grow (thanks to version control)

This gist explains how I do my PlantUML workspace in a project.

• The idea is to keep a globals directory for all diagrams to follow (like the "stylesheet" below) to keep things consistent.
• I use a stylesheet.iuml file that keeps the use of colors consistent through use of basic FOREGROUND, BACKGROUND and ACCENT colors.
• The style-presets.iuml file defines these colors so you can make "presets" or "themes" out of them.
• As stated in the stylesheet.iuml, you'll need the Roboto Condensed and Inconsolata fonts for these to work properly.
• You can choose to either run the PlantUML jar over your file/s, or use an IDE like VSCode with the PlantUML extension. Here's a preview of example-sequence.puml for example: https://imgur.com/Klk3w2F