jadsongmatos

const vec = [0,1,2,4,8,16,32,64,128];
const string = compressVec(vec);
const decompress = decompressVec(string);

function compressVec(vec) {
  let result = "";

  for (let i = 0; i < vec.length; i++) {
    // parseInt("1"+String("0000000" + vec[i].toString(2)).slice(-7), 2) == vec[i] + 128 ?
    result = result + String.fromCharCode(vec[i] + 128);

jadsongmatos

// 57.23 dec
r = ""
a = 0.23
b = 0;
for (let index = 0; index < 52; index++) {
    b = a * 2
    console.log(b)
    if(b > 1){
        a = b - 1;
        r = r + "1"

jadsongmatos

#!/bin/bash
####################################
#
# Backup TAR script.
#
####################################

find /home/jadson/Área\ de\ trabalho/ -type f | grep -v -E '*node_modules*|*App/chromium*' > /tmp/archiveFileList.txt && tar -I 'zstd --ultra -22 -T1' -cvf /home/jadson/Público/1-bkp.tar.zst -T /tmp/archiveFileList.txt && mv /tmp/archiveFileList.txt /home/jadson/Público/

jadsongmatos

// https://webbrowsertools.com/screen-size

class Screen {
  constructor() {
    ratio: 8;
  }

  gcd(a, b) {
    return 0 === b ? a : this.gcd(b, a % b);
  }

jadsongmatos

from transformers import LEDForConditionalGeneration, LEDTokenizer

tokenizer = LEDTokenizer.from_pretrained('allenai/led-large-16384')
model = LEDForConditionalGeneration.from_pretrained('allenai/led-large-16384')

inputs = tokenizer.encode("Lorem Ipsum is simply dummy text of the printing and typesetting industry.", return_tensors="pt")

# Generate Summary with higher repetition penalty
summary_ids = model.generate(inputs, num_beams=4, max_length=1024, repetition_penalty=2.0)
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)

jadsongmatos

jadsongmatos

import csv

# Define o caminho do arquivo de entrada e de saída
input_file_path = 'TXITENS.BKP'
output_file_path = 'TXITENS.CSV'

# Define os campos e seus tamanhos de acordo com a especificação
fields = [
    ("Código do Departamento", 2), ("Tipo de Produto", 1), ("Código do Item", 8), 
    ("Preço (R$/kg ou R$/Unidade)", 6), ("Dias de Validade", 3),

jadsongmatos

import re
from langchain.text_splitter import RecursiveCharacterTextSplitter
import tiktoken

# Define o limite de caracteres para cada split
chunk_size = 200

# Função para remover separadores de um texto
def remove_separators(text, separators):
    pattern = '|'.join(map(re.escape, separators))

jadsongmatos

jadsongmatos