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@olasitarska
olasitarska / pgessays.py
Created November 18, 2012 10:11
Builds epub book out of Paul Graham's essays.
# -*- coding: utf-8 -*-
"""
Builds epub book out of Paul Graham's essays: http://paulgraham.com/articles.html
Author: Ola Sitarska <ola@sitarska.com>
Copyright: Licensed under the GPL-3 (http://www.gnu.org/licenses/gpl-3.0.html)
This script requires python-epub-library: http://code.google.com/p/python-epub-builder/
"""
import akka.actor.IO._
import akka.actor.{Props, IO, IOManager, Actor, ActorSystem}
import akka.event.Logging
import akka.util.ByteString
import java.net.InetSocketAddress
class TCPEchoServer(port: Int) extends Actor {
val log = Logging(context.system, this)
val state = IterateeRef.Map.async[IO.Handle]()(context.dispatcher)
@karpathy
karpathy / min-char-rnn.py
Last active March 31, 2026 02:45
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
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)
@adambene
adambene / ThreadStateMachine.java
Created August 23, 2016 16:59
state machine example implementation in Java
package com.adambene.gist;
import static com.adambene.gist.ThreadStateMachine.Transition.CREATE;
import static com.adambene.gist.ThreadStateMachine.Transition.FINISH;
import static com.adambene.gist.ThreadStateMachine.Transition.RESUME;
import static com.adambene.gist.ThreadStateMachine.Transition.WAIT;
import java.util.logging.Level;
import java.util.logging.Logger;
@awjuliani
awjuliani / SimplePolicy.ipynb
Created September 11, 2016 00:20
Policy gradient method for solving n-armed bandit problems.
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@serithemage
serithemage / pycaret.ipynb
Last active September 8, 2024 03:30
PyCaretํŠœํ† ๋ฆฌ์–ผ-ํšŒ๊ท€.ipynb
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"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.
@karpathy
"""
import os # os.path.exists
import math # math.log, math.exp