q3k

0810 b' from '
0678 b' ssh2'
00d8 b'%.48s:%.48s():%d (pid=%ld)\x00'
0708 b'%s'
0108 b'/usr/sbin/sshd\x00'
0870 b'Accepted password for '
01a0 b'Accepted publickey for '
0c40 b'BN_bin2bn\x00'
06d0 b'BN_bn2bin\x00'
0958 b'BN_dup\x00'

dorianmariecom

name: CI
on: push
jobs:
  brakeman:
    name: Brakeman
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: ruby/setup-ruby@v1
        with:

kaspth

create_table :stowaway_records do |t|
  t.string :record_type,      null: false
  t.jsonb :record_attributes, null: false, default: {}
  t.timestamps
  t.index :record_type
end

class Stowaway::Record < ActiveRecord::Base
  def self.preserve(record)
    create! record_type: record.class, record_attributes: record.attributes

smileart

Euruko 2023

Official website: https://2023.euruko.org

Agenda: https://2023.euruko.org/agenda

Place: Vilnius, Vilnius Gediminas Technical University, 🗺️ → https://2023.euruko.org/map

JLarky

Comparing install speed with cached deps

lower is better

Data

NPM

cpursley

PostgreSQL is Enough

• Simplify: move code into database functions
• Just Use Postgres for Everything
• PostgreSQL is the worlds’ best database
• Postgres is eating the database world
• Hacker News discussion

Background and Cron Jobs

schacon

require 'rugged'

# Your specified file is the first argument
file_path = ARGV[0]

repo = Rugged::Repository.discover(File.dirname(file_path))
walker = Rugged::Walker.new(repo)
walker.push(repo.head.target.oid)
walker.sorting(Rugged::SORT_TOPO)

stufro

# spec.cr
require "spectator"
require "./spec_helper"

Spectator.describe OrderCalculator do
  inject_mock Database
  def_mock(Product)

  it "multiplies the product price by given quantity" do
    product = new_mock(Product)

rain-1

This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

• Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.

kddnewton

# frozen_string_literal: true

require "bundler/inline"

gemfile do
  source "https://rubygems.org"
  gem "json_pure"
  gem "benchmark-ips"
end