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#!/usr/bin/env python3
import requests
import json
from typing import List, Dict, Union, Optional
import subprocess
import argparse
from rich.console import Console
from rich.table import Table
from rich.panel import Panel
@kalomaze
kalomaze / llama_sillytavern_guide.md
Last active September 14, 2024 16:36
Simple Llama + SillyTavern Setup Guide

Simple Llama + SillyTavern Setup Guide

This guide is meant for Windows users who wish to run Facebook's Llama AI language model on their own PC locally. Our focus will be on character chats, reminiscent of platforms like character.ai / c.ai, using Llama architecture models. Most recently, in late 2023 and early 2024, Mistral AI has released high quality models that are based of the Llama architecture, and will work in the same way if you choose to use them.

  • Requirements

    • Windows operating system (may make Mac version of the guide later)
    • GPU with at least a few gigabytes of VRAM (NVIDIA graphics cards recommended)
  • Sufficient regular RAM for a model (system memory)

@staberas
staberas / interactive_websearch_chat.py
Last active August 7, 2024 04:40
interactive_websearch_chat.py
# This script requires to have some basic Python skills
# - Install python dependencies (thanks to TitwitMuffbiscuit on reddit) :
# pip install nltk beautifulsoup4 googlesearch-python trafilatura wolframalpha
#
# If you get this error "Resource punkt not found", it's because Punkt sentence tokenizer for Natural Language Toolkit is missing.
# Edit the file and add this before
# from nltk.tokenize import word_tokenize ,
# it will download the necessary english.pickle:
# import nltk
# nltk.download('punkt')
@nateraw
nateraw / stable_diffusion_walk.py
Created August 18, 2022 05:59
Walk between stable diffusion text prompts
"""
Built on top of this gist by @karpathy:
https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355
stable diffusion dreaming over text prompts
creates hypnotic moving videos by smoothly walking randomly through the sample space
example way to run this script:
$ python stable_diffusion_walk.py --prompts "['blueberry spaghetti', 'strawberry spaghetti']" --seeds 243,523 --name berry_good_spaghetti
@recih
recih / Mixamo.js
Last active November 30, 2020 14:54 — forked from gnuton/Mixamo.js
Script which downloads all mixamo animations for one character.
// Mixamo Animation downloadeer
// The following script make use of mixamo2 API to download all anims for a single character that you choose.
// The animations are saved with descriptive long names instead of the short ones used by default by mixamo UI.
//
// This script has been written by [email protected] and the author is not responsible of its usage
//
// How to use this script
// 1. Browse mixamo.com
// 2. Log in
// 3. Open JS console (F12 on chrome)
@gnuton
gnuton / Mixamo.js
Last active January 22, 2024 07:29
Script which downloads all mixamo animations for one character.
// Mixamo Animation downloadeer
//
// Author: Antonio Aloisio <[email protected]>
// Contributions: kriNon
//
// The following script make use of mixamo2 API to download all anims for a single character that you choose.
// The animations are saved with descriptive long names instead of the short ones used by default by mixamo UI.
//
// This script has been written by [email protected] and the author is not responsible of its usage
//
@galek
galek / pbr.glsl
Created November 4, 2015 11:10
PBR GLSL SHADER
in vec2 v_texcoord; // texture coords
in vec3 v_normal; // normal
in vec3 v_binormal; // binormal (for TBN basis calc)
in vec3 v_pos; // pixel view space position
out vec4 color;
layout(std140) uniform Transforms
{
mat4x4 world_matrix; // object's world position
@knowuh
knowuh / photo.py
Last active May 28, 2023 10:49
Blender script to turn an image data block into 3D cubes...
import bpy
import colorsys
"""
cubify-image.py - Turns each pixel of an image into a scaled cube.
Noah Paessel | @knowuh - updated on 2022-02-13 (test w Blender 3.1b)
MIT license http://opensource.org/licenses/MIT
WARNING: This script will generate a thousands objects (one per image pixel)
I recommend only using it with image with less than 40,000 pixels (200x200).