Google Colaboratory

Overview and Use Case

Google Colab or “Colaboratory” is good for students, data scientists, and AI researchers and also for running Python programs in a cloud environment which can be shared with others allowing collaboration. Machines are automatically setup and provide different CPU, memory, graphicals processing unit (GPU) features. Machines also include common Python data science libraries.

Example Getting Started

import pandas as pd

last_names = ['Connor', 'Connor', 'Reese']
first_names = ['Sarah', 'John', 'Kyle']
df = pd.DataFrame({
  'first_name': first_names,
  'last_name': last_names,
})
df

first_name last_name 0 Sarah Connor 1 John Connor 2 Kyle Reese

Running commands and installing programs

Google Collab support running shell commands for example to install modules, install programs. Example is from Free Ollama GPU - Reddit

If using a GPU, change the runtime type to include a GPU/TPU

# Run in Google Colab
!curl -fsSL https://molodetz.nl/retoor/uberlama/raw/branch/main/ollama-colab-v2.sh | sh

# It will execute this script on the machine
# Install Ollama.
curl -fsSL https://ollama.com/install.sh | sh

# Start Ollama on the background.
nohup ollama serve > ollama.log 2>&1 &

# Wait a second.
sleep 2

# Your model.
ollama pull qwen2.5-coder:14b

# ... other shell commands like pip installs, uv tool
pip install polars
uv --help