adrienbrault

# Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp

# Build it
make clean
LLAMA_METAL=1 make

# Download model
export MODEL=llama-2-13b-chat.ggmlv3.q4_0.bin

hyperupcall

// I'm tired of extensions that automatically:
// - show welcome pages / walkthroughs
// - show release notes
// - send telemetry
// - recommend things
//
// This disables all of that stuff.
// If you have more config, leave a comment so I can add it!!

{

moodymudskipper

# You'll also need to add roxygen2 to Suggests in the DESCRIPTION file to satisfy checks
# or just call `usethis::use_package("roxygen2", "Suggests")`

# first we define the tag used in examples in the doc ----------------------------------------------

#' @export
#' @importFrom roxygen2 roxy_tag_parse
roxy_tag_parse.roxy_tag_tip <- function(x) {
  roxygen2::tag_markdown(x)
}

geoffjay

#!/bin/bash -e

QUERY='{
  search(type: ISSUE, query: "is:pr state:closed repo:clio/grow", first: 100) {
    nodes {
      ... on PullRequest {
        title
        number
        additions
        deletions

andrewmoles2

# script to upgrade R and re-install all (or at least most) packages

# Pre-upgrade: save your packages as an rds file
my_pkg <- pak::pkg_list()

# if loaded from RStudio 
#here::here("R", "update_packages", "my_packages.rds") 
# if loaded from finder
saveRDS(object = my_pkg, file = "my_packages.rds") 

HenrikBengtsson

cran_days_since_release <- function(pkg, now = Sys.time()) {
  db <- rbind(tools:::CRAN_archive_db()[[pkg]], tools:::CRAN_current_db()[pkg,])
  now - sort(db$mtime, decreasing = TRUE)
}

# The CRAN rule is maximum 7 existing releases within the last 180 days
# https://github.com/wch/r-source/blob/tags/R-4-1-2/src/library/tools/R/QC.R#L7990-L8007
cran_wait_needed <- function(pkg, max = 7L, limit = 180, now = Sys.time()) {
  since <- cran_days_since_release(pkg, now = now)
  too_new <- since[since <= limit]

walkerke

library(tidycensus)
library(ggiraph)
library(tidyverse)
library(patchwork)

vt_income <- get_acs(
  geography = "county",
  variables = "B19013_001",
  state = "VT",
  year = 2019,

elliottmorris

#' Description
#' This file runs a live election-night forecast based on The Economist's pre-election forecasting model
#' available at projects.economist.com/us-2020-forecast/president.
#' It is resampling model based on https://pkremp.github.io/update_prob.html.
#' This script does not input any real election results! You will have to enter your picks/constraints manually (scroll to the bottom of the script).
#' 
#' Licence
#' This software is published by *[The Economist](https://www.economist.com)* under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by *The Economist* are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).
#' The licences include only the data and the software authored by *The Economist*, and do not cover any *Economist* content or third-party data or content made available using the software. More information about licensing, syndication and the copyright of *Economist* content can be fou

MattNickodemus

Setting up RStudio for Oracle pull using odbc on maxOS Catalina

1. install unixodbc using homebrew

You can install homebrew here. Once that is done, run this in the terminal.

brew install unixodbc

2. Download instant client from Oracle

johnburnmurdoch

read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv") %>%
  gather(date, cases, 5:ncol(.)) %>%
  mutate(date = as.Date(date, "%m/%d/%y")) %>%
  group_by(country = `Country/Region`, date) %>%
  summarise(cases = sum(cases)) %>%
  filter(country != "Others" & country != "Mainland China") %>%
  bind_rows(
    tibble(country = "Republic of Korea", date = as.Date("2020-03-11"), cases = 7755)
  ) %>%
  group_by(country) %>%