MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

veekaybee

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

adamwiggins

Make it real

Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discuss around concrete examples, not hand-waving abstractions. Don't say you did something, provide a URL that proves it.

Ship it

Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.

Do it with style

CMCDragonkai

HTTP Streaming (or Chunked vs Store & Forward)

The standard way of understanding the HTTP protocol is via the request reply pattern. Each HTTP transaction consists of a finitely bounded HTTP request and a finitely bounded HTTP response.

However it's also possible for both parts of an HTTP 1.1 transaction to stream their possibly infinitely bounded data. The advantages is that the sender can send data that is beyond the sender's memory limit, and the receiver can act on

rtt

Tinder API documentation

Note: this was written in April/May 2014 and the API may has definitely changed since. I have nothing to do with Tinder, nor its API, and I do not offer any support for anything you may build on top of this. Proceed with caution

http://rsty.org/

I've sniffed most of the Tinder API to see how it works. You can use this to create bots (etc) very trivially. Some example python bot code is here -> https://gist.github.com/rtt/5a2e0cfa638c938cca59 (horribly quick and dirty, you've been warned!)

mfd

@font-face {
  font-family: GT Walsheim Pro;
  src: local("GT Walsheim Pro Regular"),local("GTWalsheimProRegular"),url(GTWalsheimProRegular.woff2) format("woff2"),url(GTWalsheimProRegular.woff) format("woff"),url(GTWalsheimProRegular.ttf) format("truetype");
  font-weight: 400;
  font-style: normal
}

@font-face {
  font-family: GT Walsheim Pro;
  src: local("GT Walsheim Pro Bold"),local("GTWalsheimProBold"),url(GTWalsheimProBold.woff2) format("woff2"),url(GTWalsheimProBold.woff) format("woff"),url(GTWalsheimProBold.ttf) format("truetype");

tabishiqbal

<%= form_with(model: team) do |form| %>
  <div>
    <%= form.label :name %>
    <%= form.text_field :name, class: "input" %>
  </div>

  <div>
    <%= f.select :user_id, {}, {placeholder: "Select user"}, {class: "w-full", data: { controller: "select", select_url_value: users_path }} %>
  </div>

adrienbrault

# 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

python273

import os
os.environ["OPENAI_API_KEY"] = ""

from flask import Flask, Response, request
import threading
import queue

from langchain.chat_models import ChatOpenAI
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.schema import AIMessage, HumanMessage, SystemMessage

jbenet

a simple git branching model (written in 2013)

This is a very simple git workflow. It (and variants) is in use by many people. I settled on it after using it very effectively at Athena. GitHub does something similar; Zach Holman mentioned it in this talk.

Update: Woah, thanks for all the attention. Didn't expect this simple rant to get popular.