Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.
Avoid being a link dump. Try to provide only valuable well tuned information.
Neural network links before starting with transformers.
# Install QEMU OSX port with ARM support | |
sudo port install qemu +target_arm | |
export QEMU=$(which qemu-system-arm) | |
# Dowload kernel and export location | |
curl -OL \ | |
https://github.com/dhruvvyas90/qemu-rpi-kernel/blob/master/kernel-qemu-4.1.7-jessie | |
export RPI_KERNEL=./kernel-qemu-4.1.7-jessie | |
# Download filesystem and export location |
# You don't need Fog in Ruby or some other library to upload to S3 -- shell works perfectly fine | |
# This is how I upload my new Sol Trader builds (http://soltrader.net) | |
# Based on a modified script from here: http://tmont.com/blargh/2014/1/uploading-to-s3-in-bash | |
S3KEY="my aws key" | |
S3SECRET="my aws secret" # pass these in | |
function putS3 | |
{ | |
path=$1 |
# Basic Dante Socks5 Setup, Debian | |
apt-get update | |
apt-get install make gcc | |
cd /usr/src | |
# get newest from http://www.inet.no/dante/download.html | |
wget http://www.inet.no/dante/files/dante-1.4.1.tar.gz |
""" | |
Settings for root logger. | |
Log messages will be printed to console and also to log file (rotated, with | |
specified size). All log messages from used libraries will be also handled. | |
Three approaches for defining logging settings are used: | |
1. using logging classes directly (py25+, py30+) | |
2. using fileConfig (py26+, py30+) | |
3. using dictConfig (py27+, py32+) | |
Choose any variant as you like, but keep in mind python versions, that |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real