Ollama on Google Colab - A Game-Changer!



AI Summary

  • Concerns about machine power for hosting large language models (LLMs)
    • Solution: Use Google’s service to run LLMs
  • Tools and services needed:
    • Olama: Framework for running LLMs locally
      • Open source and easy to install
    • Google Colab: Cloud-based platform for Python code and Jupyter notebooks
      • Requires Google account
      • Colab Pro subscription recommended for GPU servers
    • Enro: Provides public URL for local web applications
      • Free account required
  • Setup process:
    • Run Olama on both local machine and Google Colab
    • Use HTTP requests to interact with Olama
    • Use Enro to tunnel local server to the internet
    • Local Olama installation interacts with public URL
  • Downsides:
    • Privacy concerns with Google Colab and Enro
    • Cost of Colab Pro subscription
  • Personal experience:
    • MacBook Air with 8 GB of RAM struggles with LLMs
    • Colab Pro subscription is a cost-effective solution
  • Step-by-step setup guide:
    1. Log into Enro and get authentication token and domain
    2. Open Jupyter Notebook on Colab
    3. Insert Enro authentication code into the notebook
    4. Execute notebook to set up Olama on Colab and link to Enro URL
    5. Connect local Olama to public Enro URL
    6. Run Olama
  • Additional steps for day-to-day usage:
    • Disconnect and delete runtime in Colab when finished
    • Option to store models on Google Drive for convenience
    • Use Olama Web UI for a chat-like interface
  • Conclusion:
    • Video provides guidance on installation and usage of Olama with Google Colab and Enro.