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.
| require 'sidekiq/api' | |
| # 1. Clear retry set | |
| Sidekiq::RetrySet.new.clear | |
| # 2. Clear scheduled jobs | |
| Sidekiq::ScheduledSet.new.clear |
| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
| // All thanks goes to: http://stackoverflow.com/a/25733922 | |
| var ProtoBuf = require("protobufjs"); | |
| var http = require('http'); | |
| // MTA Realtime endpoint http://datamine.mta.info/mta_esi.php?key=xxxx | |
| var feedUrl = "..."; | |
| // Initialize from .proto file | |
| // Requires nyct-subway.proto and gtfs-realtime.proto |
Note: replace {{server}} with your domain or ip
ssh -i key.pem ec2-user@{{server}}
sudo -i
| =Navigating= | |
| visit('/projects') | |
| visit(post_comments_path(post)) | |
| =Clicking links and buttons= | |
| click_link('id-of-link') | |
| click_link('Link Text') | |
| click_button('Save') | |
| click('Link Text') # Click either a link or a button | |
| click('Button Value') |