Hitesh Aidasani htsh

Some remarks on Large Language Models

Yoav Goldberg, January 2023

Audience: I assume you heard of chatGPT, maybe played with it a little, and was imressed by it (or tried very hard not to be). And that you also heard that it is "a large language model". And maybe that it "solved natural language understanding". Here is a short personal perspective of my thoughts of this (and similar) models, and where we stand with respect to language understanding.

Intro

Around 2014-2017, right within the rise of neural-network based methods for NLP, I was giving a semi-academic-semi-popsci lecture, revolving around the story that achieving perfect language modeling is equivalent to being as intelligent as a human. Somewhere around the same time I was also asked in an academic panel "what would you do if you were given infinite compute and no need to worry about labour costs" to which I cockily responded "I would train a really huge language model, just to show that it doesn't solve everything!". We

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.

Setup

Create a new directory with these three files (requirements.txt, main.py, README.md)
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python main.py
Update main() to run the example prompt chains

	# 2023-11-27 MIT LICENSE

	Here's the open source version of my ChatGPT game MonkeyIslandAmsterdam.com.

	It's an unofficial image+text-based adventure game edition of Monkey Island in Amsterdam, my home town.

	Please use it however you want. It'd be nice to see more ChatGPT-based games appear from this. If you get inspired by it, please link back to my X https://x.com/levelsio or this Gist so more people can do the same!

	Send me your ChatGPT text adventure game on X, I'd love to try it!

	from fastapi import Request, HTTPException
	from pydantic import BaseModel, BaseModel, HttpUrl
	from modal import Secret, App, web_endpoint, Image
	from typing import Optional, List
	from example import proposal
	import os

	app = App(name="circleback", image=Image.debian_slim().pip_install("openai", "pydantic", "fastapi"))

	class Attendee(BaseModel):