sammcj

import asyncio
import aiohttp
import os
from pathlib import Path
import logging
from bs4 import BeautifulSoup
from typing import List, Dict
from dataclasses import dataclass
from datetime import datetime
import time

rmtbb

#!/bin/bash

# Define the main export folder
export_folder=~/Desktop/iMessages_Export
mkdir -p "$export_folder"

# Part 1: Generate the CSV file
echo "Generating CSV file..."

sqlite3 ~/Library/Messages/chat.db <<EOF

jrruethe

#!/usr/bin/env ruby

# https://asmirnov.xyz/vram
# https://vram.asmirnov.xyz

require "fileutils"
require "json"
require "open-uri"

# https://huggingface.co/spaces/NyxKrage/LLM-Model-VRAM-Calculator/blob/main/index.html

davidmezzetti

from txtai import Embeddings, LLM

# Data to index
data = [
  "US tops 5 million confirmed virus cases",
  "Canada's last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg",
  "Beijing mobilises invasion craft along coast as Taiwan tensions escalate",
  "The National Park Service warns against sacrificing slower friends in a bear attack",
  "Maine man wins $1M from $25 lottery ticket",
  "Make huge profits without work, earn up to $100,000 a day"

Artefact2

Which GGUF is right for me? (Opinionated)

Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggerganov/llama.cpp#5962

In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.

llama.cpp feature matrix

See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix

sammcj

# https://github.com/oobabooga/text-generation-webui/blob/main/README.md
# https://github.com/oobabooga/text-generation-webui/blob/main/docs/Spell-book.md

# by default the Dockerfile specifies these versions: 3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX
# https://developer.nvidia.com/cuda-gpus you can find the version for your card here
# Tesla P100 = sm_60, sm_61, sm_62 and compute_60, compute_61, compute_62
# TORCH_CUDA_ARCH_LIST=6.0,6.1,6.2,7.0,7.5,8.0,8.6+PTX
# RTX3090 = sm_86 and compute_86 (PTX)
#8.6+PTX
# Tesla P100 = sm_60, sm_61, sm_62 and compute_60, compute_61, compute_62

ChristophCaina

#------------------------------------------------------------------------------------#
#     PIN Schematics                                                                 #
#                                                                                    #
#       GPIO-00 MCU-BOOT                                                             #
#       GPIO-01 Speaker Mute-Status                                                  #
#       GPIO-02 I2S MCLK                                                             #
#       GPIO-03 Touch-Screen TT21100 Interrupt Pin                                   #
#       GPIO-04 ILI92xxx Display DC-Pin (SPI: CLK-Pin)                               #
#       GPIO-05 ILI92xxx Display CS-Pin (SPI: MOSI-Pin)                              #
#       GPIO-06 ILI92xxx Display SDA                                                 #

thimslugga

Setup Docker on Amazon Linux 2023

The following guide is for setting up Docker with docker-compose v2 on Amazon Linux 2023. The steps are intendend for AL2023 on EC2 but should mostly work for the AL2023 VMs running on other hypervisors.

Overview of Updating Amazon Linux 2023

Check for new updates

Get the hosts current Amazon Linux 2023 release:

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

allenporter

---
blueprint:
  name: Conversation agent Agenda Notification
  description:
    Conversation agent generates a notification based on the upcoming calendar
    agenda, location, and weather information.
  domain: automation
  input:
    notify_time:
      name: Notification time