veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

chirag-agarwall

def image_name_to_netid():
    # Map imagenet names to their netids
    input_f = open("./imagenet_validation_imagename_labels.txt")
    label_map = {}
    netid_map = {}
    for line in input_f:
        parts = line.strip().split(" ")
        label_map[parts[0]] = parts[1]
        netid_map[parts[0]] = parts[2]
    return label_map, netid_map

anguyen8

#!/bin/bash

# Anh Nguyen <[email protected]>
# 2016-04-30
# MIT License

# This script takes in same-size images from a folder and make a crossfade video from the images using ffmpeg.
# Make sure you have ffmpeg installed before running.

# The output command looks something like the below, but for as many images as you have in the folder.

ericdouglas

// 4 spaces to 2 spaces
%s;^\(\s\+\);\=repeat(' ', len(submatch(0))/2);g

// Tab to 2 spaces
:%s/\t/  /g

elranu

/**
 * Mariano Julio Vicario aka Ranu - TW: @el_ranu
 * http://www.ranu.com.ar
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software