vitorcalvi

# Step 1: Install the Termux app
# Download and install the Termux app from Google Play Store or F-Droid

# Step 2: Open Termux and run the following commands

# Update and upgrade existing packages
apt update && apt upgrade -y

# Install necessary packages
apt install clang python fftw libzmq freetype libpng pkg-config libcrypt -y

vitorcalvi

Installing docker on Ubuntu 20.04 / 22.04

Full reference here: https://docs.docker.com/engine/install/ubuntu/

Setup the repository

sudo apt-get update
sudo apt-get install apt-transport-https ca-certificates curl gnupg lsb-release

Add Docker’s official GPG key:

vitorcalvi

Shrink code
Requirements:
Combined import statements into a single line where possible.
Removed unnecessary whitespace and comments.
Inlined some logic to reduce the number of lines.
Used list comprehensions and generator expressions to simplify the code.
Shortened variable names where readability was not compromised.

vitorcalvi

NAME=$(basename "$(ls -td ~/Desktop/webllama/*/ | head -1)") && conda create -n "$NAME" python=3.10 -y && conda activate "$NAME" && read -p "Install packages from requirements.txt? (yes/no): " choice && [[ "$choice" == "yes" ]] && pip install -r requirements.txt

vitorcalvi

import os
import json
import argparse
from huggingface_hub import snapshot_download, HfApi

# Parse command-line arguments
parser = argparse.ArgumentParser(description="Convert and upload a model to Hugging Face Hub.")
parser.add_argument("--hf_token", type=str, required=True, help="Hugging Face token")
parser.add_argument("--model_id", type=str, required=True, help="Model ID on Hugging Face Hub")
parser.add_argument("--outtype", type=str, required=True, help="Output type for the conversion (e.g., q8_0, f16, f32)")

vitorcalvi

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

# Function to print messages

vitorcalvi

# Version 1
#env_name='mlx-chat-app'; 
#conda deactivate &&  conda remove --name "$env_name" --all -y && \
#conda create -n "$env_name" python=3.10 -y && conda activate "$env_name" && 
# pip install tensorflow-macos tensorflow-metal &&
# pip install -r requirements.txt

read -p "Enter the name of the conda environment: " env_name && conda deactivate && conda remove --name "$env_name" --all -y && conda create -n "$env_name" python=3.10 -y && conda activate "$env_name" && pip install -r requirements.txt

vitorcalvi

#!/bin/bash


sudo apt update && sudo apt full-upgrade -y


# Install cockpit and its components, netdata, git-lfs, and npm
sudo apt install "cockpit" "cockpit-machines" "cockpit-storaged" "cockpit-packagekit" "cockpit-networkmanager" "cockpit-system" -y
sudo apt install netdata -y && sudo apt install git-lfs -y && sudo apt install npm -y

vitorcalvi

#!/bin/bash

set -eo pipefail

# Function to install Xcode Command Line Tools
install_xcode_cli() {
  echo "Installing Xcode Command Line Tools..."
  xcode-select --install
}

vitorcalvi

# List all Conda environments
conda env list

# Capture the list of environment names and loop through them
while IFS= read -r line; do
    # Extract the environment name from each line
    name=$(echo "$line" | cut -d ' ' -f 1)
    
    # Skip the first line (header) and the base environment
    if [ "$name" != "#" ] && [ "$name" != "base" ]; then