eriknomitch

aider-commit

A simple wrapper for using aider to create commits with automatically generated messages using AI. Includes a few extra checks and outputs.

Installation

1. Set up aider
2. Add the function to your ~/.zshrc or ~/.bashrc.

Usage

kylemcdonald

import pyaudio
import audioop

p = pyaudio.PyAudio()

stream = p.open(format=pyaudio.paInt16,
                channels=1,
                rate=44100,
                input=True,
                frames_per_buffer=1024)

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

goodside

"""
Toy demonstration of chain-of-thought and consensus prompting using OpenAI API.

© Riley Goodside 2022
"""

import os
import re
from statistics import mode

jachiam

# 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

ibrennan

import { useState, useEffect, useCallback } from 'react';

export const useVisbilityState = () => {
  const [visibilityState, setVisibilityState] = useState(null);

  const handleVisbilityChange = useCallback(() => {
    setVisibilityState(document.visibilityState);
  }, [setVisibilityState]);

  useEffect(() => {

ramast

#!/usr/bin/env python3
# Based on code from these stackoverflow answers:
# https://askubuntu.com/questions/60837/record-a-programs-output-with-pulseaudio/910879#910879
import re
import subprocess
import sys
import os
import signal
from time import sleep

wonderbeyond

import six
from peewee import Model, FieldAccessor
from playhouse.postgres_ext import BinaryJSONField


class GForeignKeyAccessor(FieldAccessor):
    def get_rel_instance(self, instance):
        value = instance.__data__.get(self.name)
        model_name = value['model']
        rel_model = self.field.allowed_types[model_name]

soxofaan

Google Apps Script to automatically delete mails with a certain label after a certain time

Usage

0. Think of a deletion scheme and create GMail labels accordingly (e.g. I use labels 'todelete/after1week', 'todelete/after1month' and 'todelete/after3months' here)
1. set up filters in GMail to flag desired mails with these labels
2. create a Google Apps Script with this script (adapt function names, labels and day offsets appropriatedly) and set up triggers as desired

Disclaimer

kevinzakka

"""
Create train, valid, test iterators for CIFAR-10 [1].
Easily extended to MNIST, CIFAR-100 and Imagenet.

[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
"""

import torch
import numpy as np