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Knut Behrends knbknb

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@rauschma
rauschma / string.md
Last active February 5, 2024 04:12

Strings

String.prototype.*

None of the string methods modify this – they always return fresh strings.

  • charAt(pos: number): string ES1

    Returns the character at index pos, as a string (JavaScript does not have a datatype for characters). str[i] is equivalent to str.charAt(i) and more concise (caveat: may not work on old engines).

@jdhitsolutions
jdhitsolutions / 1-Get-DockerDiskUsage.ps1
Last active November 10, 2023 15:51
A Powershell function that wraps Docker command line output to display disk usage. Save the files without the numeric prefix.
#requires -version 5.1
Function Get-DockerDiskUsage {
[cmdletbinding()]
[alias("gddu")]
[OutputType("Get-DockerDiskUsage.DockerDiskUsage")]
Param(
[Parameter(Position = 0, HelpMessage = "Get specific usage types. The default is All")]
[ValidateSet("Images","Containers","Volumes","Cache")]
[string[]]$Type
@isteves
isteves / tidyselect.md
Last active May 4, 2020 15:28
Trying to grok tidyselect

Trying to grok tidyselect

Key takeaways:

  • everything inside vars(...) is exactly the same as the stuff inside select(...)!!!
  • vars() is used for all scoped variants of dplyr verbs (I assume bc the variables need to “fit” into a single argument, .vars. In select(...), the ellipses take everything)
  • vars_select() is probably more of a developer-facing function (seen in select_helpers documentation)

Some "gotchas":

@chrishoerl
chrishoerl / cleanup-gitlab-pipelines.sh
Last active September 13, 2024 13:00
Bulk delete gitlab pipelines older than a given date
#!/bin/bash
# Purpose: Bulk-delete GitLab pipelines older than a given date
# Author: github.com/chrishoerl
# GitLab API: v4
# Requirements: jq must be instaled ($ sudo apt install jq)
# API example: https://gitlab.example.com/api/v4/projects
# API example: https://gitlab.example.com/api/v4/projects/<projectid>/pipelines
#
# NOTE: Script is just a dryrun. To really delete pipelines, simply uncomment line 49 to activate
#
@hadley
hadley / dplyr-summarise.R
Last active March 16, 2025 18:52
# What's the most natural way to express this code in base R?
library(dplyr, warn.conflicts = FALSE)
mtcars %>%
group_by(cyl) %>%
summarise(mean = mean(disp), n = n())
#> # A tibble: 3 x 3
#> cyl mean n
#> <dbl> <dbl> <int>
#> 1 4 105. 11
#> 2 6 183. 7
@wch
wch / pluck_recursive.R
Created March 10, 2022 04:21
From a tree, recursively pluck all elements with a particular name
# @drob's version from https://twitter.com/drob/status/1501747414780239879
pluck_recursive <- function(lst, name) {
if (is.list(lst)) {
if (!is.null(lst[[name]])) {
return(lst[[name]])
}
return(unname(unlist(purrr::map(lst, pluck_recursive, name))))
}
}
@georgestagg
georgestagg / mandeldrop.R
Created July 26, 2022 19:03
Mandelbrot set, transformed into a teardrop shape, in R and Rcpp
Rcpp::sourceCpp("mandeldrop.cpp")
xlims=c(-0.65,0.65)
ylims=c(-0.6,2.2)
m <- mandeldrop(xlims[[1]], xlims[[2]], ylims[[1]], ylims[[2]], 1560, 2160, 512)
# Colour palette from https://stackoverflow.com/q/48069990
rainbow=c(rgb(0.47,0.11,0.53),rgb(0.27,0.18,0.73),rgb(0.25,0.39,0.81),rgb(0.30,0.57,0.75),rgb(0.39,0.67,0.60),rgb(0.51,0.73,0.44),rgb(0.67,0.74,0.32),rgb(0.81,0.71,0.26),rgb(0.89,0.60,0.22),rgb(0.89,0.39,0.18),rgb(0.86,0.13,0.13))
cols=c(colorRampPalette(rainbow)(100),rev(colorRampPalette(rainbow)(100)),"black")
@knbknb
knbknb / ubuntu-custom-setup.sh
Last active March 8, 2023 14:13 — forked from riccardopedrielli/ubuntu-workstation-setup.sh
Ubuntu workstation setup
#!/usr/bin/env bash
set -Eeu
trap 'STATUS=${?}; echo "${0}: Error on line ${LINENO}: ${BASH_COMMAND}"; exit ${STATUS}' ERR
trap 'rm -rf ${tempDir}' EXIT
readonly supportedUbuntuVersion="22.04"
readonly tempDir="/tmp/setup"
readonly devDir="${HOME}/dev"
readonly scriptsDir="${devDir}/scripts"
@yoavg
yoavg / rl-for-llms.md
Last active April 20, 2025 17:47

Reinforcement Learning for Language Models

Yoav Goldberg, April 2023.

Why RL?

With the release of the ChatGPT model and followup large language models (LLMs), there was a lot of discussion of the importance of "RLHF training", that is, "reinforcement learning from human feedback". I was puzzled for a while as to why RL (Reinforcement Learning) is better than learning from demonstrations (a.k.a supervised learning) for training language models. Shouldn't learning from demonstrations (or, in language model terminology "instruction fine tuning", learning to immitate human written answers) be sufficient? I came up with a theoretical argument that was somewhat convincing. But I came to realize there is an additional argumment which not only supports the case of RL training, but also requires it, in particular for models like ChatGPT. This additional argument is spelled out in (the first half of) a talk by John Schulman from OpenAI. This post pretty much

@jthomasmock
jthomasmock / copilot_keyword.R
Created September 13, 2023 01:35
Solving the Keyword game with R, with a little help from RStudio and Copilot!
library(tidyverse)
library(stringr)
library(jsonlite)
# create a function to solve the Keyword game
# this game uses a 6 letter horizontal word at the
# intersection of 6 other words, where a missing letter from each of the vertical words
# accounts for one letter of the mystery 6 letter length horizontal word
# how to play