dhh

# THIS LINUX SETUP SCRIPT HAS MORPHED INTO A WHOLE PROJECT: HTTPS://OMAKUB.ORG
# PLEASE CHECKOUT THAT PROJECT INSTEAD OF THIS OUTDATED SETUP SCRIPT.
#
#

# Libraries and infrastructure
sudo apt update -y
sudo apt install -y \
	docker.io docker-buildx \
	build-essential pkg-config autoconf bison rustc cargo clang \

alexedwards

package cache

import (
    "sync"
    "time"
)

// Cache is a basic in-memory key-value cache implementation.
type Cache[K comparable, V any] struct {
    items map[K]V     // The map storing key-value pairs.

jart

#!/bin/sh
# rename-pictures.sh
# Author: Justine Tunney <jtunney@gmail.com>
# License: Apache 2.0
#
# This shell script can be used to ensure all the images in a folder
# have good descriptive filenames that are written in English. It's
# based on the Mistral 7b and LLaVA v1.5 models.
#
# For example, the following command:

skrymets

cssclass
cornell-note

Cues

Notes

The Cornell Note-taking System is a popular and effective method for organizing and summarizing information during lectures, readings, or any other form of learning.

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

MarkRoddy

/* 
  Usage: you'll want to search for the strings <bucket> and <prefix>, and insert the S3 bucket where your access
  logs are being delivered. Use (or delete) <prefix> to filter to a subset of your logs.
*/

 
/*
  These commented out configuration settings you can either run  yourself in the REPL and source this file using
  `.read parse_s3_access_logs.sql`, or you can uncomment them and supply values for yourself.

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

softwaredoug

Solr needs opinions, because Solr documentation gives you way too many options. It's hard to navigate the best practices for using Solr. Some of my opinions based on dozens of Solr projects :)

Prefer preloading static, classic config files over managed schema, config API, or schemaless

Schema files are a good thing. They are declarative, and not letting them change at runtime prevents all kinds of security issues. Further, classic schema / solrconfig support all of Solr's functionality and are well documented with tons of examples online in blog articles and stackoverflow. Using managed schema or the config API takes a lot of experimentation.

Static configurations can also be easily version controlled. As I've learned as a long time Elasticsearch user, this is one of Solr's advantages. Having an API for changing every underlying config option of your index means finding the code that made the change is rather time consuming.

Static configuration is also good separation of concerns. You cleanly separate

jbaiter

#!/usr/bin/env python3
# coding=utf8
"""
CFE file layout:

    Header:
        CodecHeader:
            Magic               [4byte uint32]
            Codecname           [?byte String]
            Version             [4byte uint32]

mholt

// Package main is a sample macOS-app-bundling program to demonstrate how to
// automate the process described in this tutorial:
//
// https://medium.com/@mattholt/packaging-a-go-application-for-macos-f7084b00f6b5
//
// Bundling the .app is the first thing it does, and creating the DMG is the
// second. Making the DMG is optional, and is only done if you provide
// the template DMG file, which you have to create beforehand.
//
// Example use: