I installed the Google Drive desktop app in order to sync files between my computer and the cloud. I found that you could right-click a file, hover over Drive File Stream, and select an option: Available offline; Online only (default) But even when Online only is selected, large files still persist on my computer. Clear cache directory Create a Colab Notebook. Open Google Colab. Click on ‘New Notebook’ and select Python 2 notebook or Python 3 notebook. Open Google Drive. Create a new folder for the project. Click on ‘New Step2 : Open your Google drive account (primary) where all your file exists. Step3 : Share that particular holder to your secondary Gmail account. Step4 : Open your secondary Gmail account, select the shared folder and copy all the files with the extension. Step5 : Now go to Primary account folder and delete. Share. This means that emptying Google Drive trash will help you to recover space. Here’s how to do it: Click on the Trash item in the left sidebar. Click on the arrow next to “Trash” and select “Empty trash”. Confirm deletion. 4. Delete Duplicate Files from Google Drive. In the last week or two I have seen frequent disconnects while trying to run a lengthy training run. A month or two ago this seemed to be working pretty reliably. My code has definitely changed but those internal details seem unrelated to the operation of Colab. (On the other hand, I did switch my local machine from an Intel MacBook Pro running Enable billing for the project. See Google Cloud Storage (GCS) Documentation for more info. # Create a local file with data to upload. # Make a unique bucket to which we'll upload the file. # (GCS buckets are part of a single global namespace.) # Copy the file to our new bucket. # Finally, dump the contents of our newly copied file to make sure Simpler Way: As colab gives options to mount google drive. Upload images to your google drive. Click on mount drive (right side of upload icon) See files under 'drive/My Drive/'. code to check files. import glob glob.glob ("drive/My Drive/your_dir/*.jpg") Share. You can perform the following steps to clean up your Colab environment: Delete Unnecessary Files: Identify and delete any files that are no longer needed. To find what's taking up space you Clear Output and Variables: Clear the output of code cells and variables that are no longer required. This If you have space on your google drive, you can download the dataset to there and mount your google drive to colab and use the dataset that way. But if you can't do this or any other methods other commenters suggest, you might have to download Python or Miniconda onto your computer and download the dataset locally. If you are stuck at default RAM provided by Google Colab i.e, 12GBs then follow this video to upgrade the default Settings to 35 GB's of RAM and 107GB Storag EGZfCQ.