brandon-lockaby

#!/bin/bash
now=$(date +"%Y %m-%d %T ns%N")
xclip -selection clipboard -t TARGETS -o | (while IFS= read -r line; do
    echo $line
    if [[ $line = image/* ]]
    then
        notify-send "Opening ${line} with feh" -a "(•ิ_•ิ)?" -t 2000
        xclip -selection clipboard -t image/png -o | feh -
        break
    fi

brandon-lockaby

import aud

device = aud.Device()
sound = aud.Sound.sawtooth(400)
sound2 = aud.Sound.buffer(np.array([1,2,3], dtype="float32"), 44100)
handle = device.play(sound);
handle.stop();

brandon-lockaby

//FRAGMENT
#define STANDARD
#ifdef PHYSICAL
    #define IOR
    #define SPECULAR
#endif
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float roughness;
uniform float metalness;

brandon-lockaby

import bpy
from itertools import chain
import math

def convert_size(size_bytes):
   if size_bytes == 0:
       return "0B"
   size_name = ("B", "KB", "MB", "GB", "TB", "PB", "EB", "ZB", "YB")
   i = int(math.floor(math.log(size_bytes, 1024)))
   p = math.pow(1024, i)

brandon-lockaby

#!/bin/bash

# Set the threshold, duration (in seconds), and recording directory
threshold=0.2
duration=10
recording_dir="/mnt/tera/audio/NOISE2"

# Set output options
output_to_console=true
output_to_log=true

brandon-lockaby

{"id":"chatcmpl-79TNYGf2QniAFeerg2taVUVkouz3H","object":"chat.completion.chunk","created":1682492240,"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"role":"assistant"},"index":0,"finish_reason":null}]}
{"id":"chatcmpl-79TNYGf2QniAFeerg2taVUVkouz3H","object":"chat.completion.chunk","created":1682492240,"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":"As"},"index":0,"finish_reason":null}]}
{"id":"chatcmpl-79TNYGf2QniAFeerg2taVUVkouz3H","object":"chat.completion.chunk","created":1682492240,"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":" an"},"index":0,"finish_reason":null}]}
{"id":"chatcmpl-79TNYGf2QniAFeerg2taVUVkouz3H","object":"chat.completion.chunk","created":1682492240,"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":" AI"},"index":0,"finish_reason":null}]}
{"id":"chatcmpl-79TNYGf2QniAFeerg2taVUVkouz3H","object":"chat.completion.chunk","created":1682492240,"model":"gpt-3.5-turbo-0301","choices":[{"delta":{"content":" language"},"index":0,"finish_reason":null}]}
{"id":

brandon-lockaby

from exllama.model import ExLlama, ExLlamaCache, ExLlamaConfig
from exllama.lora import ExLlamaLora
from exllama.tokenizer import ExLlamaTokenizer
from exllama.generator import ExLlamaGenerator
from exllama import model_init
import argparse
import torch
import sys
import os
#import glob

brandon-lockaby

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

DEV = "cuda"

# I want a base model and this is instruct-tuned, but it will fit on my gpu
model_path = "microsoft/Phi-3-mini-128k-instruct"

model = AutoModelForCausalLM.from_pretrained(
    model_path,

brandon-lockaby