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@veekaybee
veekaybee / normcore-llm.md
Last active May 6, 2024 16:10
Normcore LLM Reads

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

Screenshot 2023-12-18 at 10 40 27 PM

Pre-Transformer Models

@adrienbrault
adrienbrault / llama2-mac-gpu.sh
Last active April 22, 2024 08:47
Run Llama-2-13B-chat locally on your M1/M2 Mac with GPU inference. Uses 10GB RAM. UPDATE: see https://twitter.com/simonw/status/1691495807319674880?s=20
# Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
# Build it
make clean
LLAMA_METAL=1 make
# Download model
export MODEL=llama-2-13b-chat.ggmlv3.q4_0.bin
@danielgross
danielgross / mathpix2gpt.py
Last active April 22, 2024 05:19
mathpix2gpt.py
import requests
import time
import os
import sys
import openai
import tiktoken
from termcolor import colored
openai.api_key = open(os.path.expanduser('~/.openai')).read().strip()
@veekaybee
veekaybee / pyscript.html
Created November 26, 2022 16:21
Testing out Pyscript
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Some plotting</title>
<link rel="stylesheet" href="https://pyscript.net/alpha/pyscript.css" />
<script defer src="https://pyscript.net/alpha/pyscript.js"></script>
<py-env>
@xirixiz
xirixiz / Set up GitHub push with SSH keys.md
Last active May 4, 2024 11:08 — forked from developius/README.md
Set up GitHub push with SSH keys

SSH keypair setup for GitHub (or GitHub/GitLab/BitBucket, etc, etc)

Create a repo.

Make sure there is at least one file in it (even just the README.md)

Generate a SSH key pair (private/public):

ssh-keygen -t rsa -C "your_email@example.com"
@baraldilorenzo
baraldilorenzo / readme.md
Last active November 21, 2023 22:41
VGG-16 pre-trained model for Keras

##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

@LeCoupa
LeCoupa / bash-cheatsheet.sh
Last active May 5, 2024 00:12
Bash CheatSheet for UNIX Systems --> UPDATED VERSION --> https://github.com/LeCoupa/awesome-cheatsheets
#!/bin/bash
#####################################################
# Name: Bash CheatSheet for Mac OSX
#
# A little overlook of the Bash basics
#
# Usage:
#
# Author: J. Le Coupanec
# Date: 2014/11/04
@johnynek
johnynek / scalding_alice.scala
Created July 18, 2014 17:15
Learn Scalding with Alice
/**
git clone https://github.com/twitter/scalding.git
cd scalding
./sbt scalding-repl/console
*/
import scala.io.Source
val alice = Source.fromURL("http://www.gutenberg.org/files/11/11.txt").getLines
// Add the line numbers, which we might want later
val aliceLineNum = alice.zipWithIndex.toList
@jboner
jboner / latency.txt
Last active May 6, 2024 07:06
Latency Numbers Every Programmer Should Know
Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD
@mikeyk
mikeyk / gist:1329319
Created October 31, 2011 22:56
Testing storage of millions of keys in Redis
#! /usr/bin/env python
import redis
import random
import pylibmc
import sys
r = redis.Redis(host = 'localhost', port = 6389)
mc = pylibmc.Client(['localhost:11222'])