Ganesh Bhat ganesh3

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

Polyglot Data Science with IPython & friends

Author: Fernando Pérez.

A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.

This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.

See the companion notebook for data preparation and setup.

This gist contains lists of modules available in

Python 3.10
Python 3.9
Python 3.8
Python 3.7
Python 3.6
Python 2.7

in AWS Lambda.

	import sys, io, os.path as path, functools as ft # basic packages
	import urllib.request as url_req, numpy as np, cv2 # extension packages
	import torch, torch.nn as nn, torchvision.ops as ops # pytorch packages

	data_path = '.' if len(sys.argv) < 2 else sys.argv[1]
	image_file_url = 'https://github.com/pjreddie/darknet/raw/master/data/dog.jpg'
	image_filename = path.join(data_path, 'dog.jpg')
	weight_file_url = 'https://pjreddie.com/media/files/yolov3.weights'
	weight_filename = path.join(data_path, 'yolov3.weights')

	#!/usr/bin/env bash
	mkdir coco
	cd coco/

	wget http://images.cocodataset.org/zips/train2017.zip
	wget http://images.cocodataset.org/zips/val2017.zip

	unzip train2017.zip
	unzip val2017.zip

	% ****************************************************************************
	% * This demonstrate how to apply blur to an RGB-image, and create a third *
	% * image which is composed partly of the original unblurred image, and *
	% * partly of the blurred image. *
	% ****************************************************************************


	% Read example image built into MATLAB
	I0 = double(imread('saturn.png'));

	var Bot = require('node-telegram-bot-api')
	var watson = require('watson-developer-cloud');
	var request = require('request');
	var config = require('./config');

	var speech_to_text = watson.speech_to_text({
	username: config.watson.username,
	password: config.watson.password,
	version: 'v1',
	url: 'https://stream.watsonplatform.net/speech-to-text/api'