MazzMa mazzma12

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

ChatGPT Resources

Context

ChatGPT appeared like an explosion on all my social media timelines in early December 2022. While I keep up with machine learning as an industry, I wasn't focused so much on this particular corner, and all the screenshots seemed like they came out of nowhere. What was this model? How did the chat prompting work? What was the context of OpenAI doing this work and collecting my prompts for training data?

I decided to do a quick investigation. Here's all the information I've found so far. I'm aggregating and synthesizing it as I go, so it's currently changing pretty frequently.

Model Architecture

This list is no longer updated, thus the information is no longer reliable.

You can see the latest version (from october 2022) here

Python relative imports in AWS Lambda fail with attempted relative import with no known parent package

The Problem

In AWS Lambda if I attempt an explicit relative import like this

.
├── lambda_file.py
└── example.py

	#!/bin/bash
	##########
	## Maintained by Laurence from CrowdSec
	## Discord: https://discord.gg/crowdsec
	## Website: https://www.crowdsec.net/
	## Docs: https://docs.crowdsec.net/
	##########

	# Linode users can use the UI to change these variables
	# Digital ocean users uncomment and change these variables

	# based on https://github.com/kylerbrown/ezdtw
	# with modifications to be fully njit-able

	import numpy as np
	from numba import njit

	@njit
	def sqeuclidean(a, b):
	return np.sum((a - b)**2)

	"""
	Gist made by Kshitij Chawla (Github name: kchawla-pi) for the Nilearn library in Feb/March 2019.
	GPLv3
	"""

	def replace_parameters(replacement_params,
	end_version='future',
	lib_name='Nilearn',
	):
	"""