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Google Colab: Limited Resources and Alternatives

What is Google Colab?
🔴 Limitations of Google Colab
✅ Solutions and Alternatives

What is Google Colab?

Google Colab (or Google Colaboratory) is a cloud-based notebook environment that allows you to run Python code without needing to install anything on your computer. It is ideal for learning, experimenting, and carrying out small to medium-sized projects with free access to GPUs and TPUs.

However, Colab has limited resources, which means that:

  • You cannot use the full power of a supercomputer.
  • The runtime of the machines is limited.
  • It may automatically disconnect you if you are inactive or consume too much memory.

🔴 Limitations of Google Colab

  1. Limited RAM and CPU

    • In the free version, you get around 12 GB of RAM and a moderate virtual CPU.
    • If you consume too much memory, the notebook can restart, and you will lose everything that is not saved.

  2. Maximum Runtime

    • Sessions in Google Colab are not permanent.
    • If you stop using the notebook for a while or run long processes, Google may close it automatically.

  3. Restricted Access to GPU and TPU

    You can use a GPU to accelerate calculations with TensorFlow or PyTorch, but access is not always guaranteed. If many people are using Colab at the same time, you might not get an available GPU.

    If you want to check if you have a GPU enabled, follow these steps:

    • Open a notebook in Google Colab.

    • Create a new code cell.

    • Write the following command and execute it (by pressing Shift + Enter or clicking the "Run" button):

    1!nvidia-smi

    If a GPU is enabled, you will see information about the model and usage of the graphics card. If nothing appears or you see an error, it means that Colab did not assign you a GPU in that session.

  4. Data Loss if the Environment is Restarted

    • If the environment disconnects or restarts, everything that was in memory (variables, models, temporary files) is lost.
    • To avoid this, save your important files to Google Drive or download them to your machine.

✅ Solutions and Alternatives

Save Files to Google Drive

To avoid losing files when Colab restarts, you can connect it to your Google Drive.

How to connect Google Colab with Google Drive?

  • Open a notebook in Google Colab.

  • Create a new code cell and execute the following command:

    1from google.colab import drive
2drive.mount('/content/drive')

What this code does is:

  • Imports the necessary Google Colab module to interact with Google Drive.
  • Mounts your Google Drive in the /content/drive folder, allowing access to your files directly from the notebook.
  • After executing this command, a window will open asking for permission to access your Google Drive.
  • You must authorize access by selecting your Google account and copying an authorization code.
  • Once authenticated, you will be able to see your Drive at the path /content/drive/My Drive/.

Work on Your Own Computer

If you need more resources or unlimited time, consider installing Jupyter Notebook or using a local environment like Anaconda. The steps to install Jupyter Notebook on your PC would be:

  • Download and install Anaconda from https://www.anaconda.com/.

  • Open Anaconda and run:

    1jupyter notebook

  • Your browser will open with an environment similar to Google Colab, but using the resources of your PC.

Google Colab Pro (Optional, but Paid)

If you need more RAM or guaranteed access to GPUs, Google offers Colab Pro (paid), which gives you better resources and more runtime.

💡 Google Colab is excellent for quick tests and small projects, but if you need more computing power, it is best to work on your own computer or on more powerful servers.