To use Colab for the course, follow the direction here:
For advanced users:
EXPERIMENTAL:
@imrandude and @deeplearner have made a script for using the Colab environment as a full Jupyter instance. To do so, please follow these steps:
Big Warning: This is experimental, not outspokenly recommended, and could be patched at a later date by Google, please use at your own discretion
- Add the two following cells into your
Colabnotebook of choice:
import subprocess def setup_colab(tok): subprocess.call(['wget', ' '-O', 'bash.sh']) subprocess.call(['sh', 'bash.sh']) get_ipython().system_raw(f'./ngrok authtoken {tok} && ./ngrok http --log=stdout 8888 > ngrok.log &') subprocess.call(['wget', ' '-O', 'bash2.sh']) subprocess.call(['sh', 'bash2.sh'])
def end_session(): subprocess.call(['wget', ' '-O', 'bash3.sh']) subprocess.call(['sh', 'bash3.sh'])
- To spin up your server, run
setup_colab(tok)and pass in your server token.
- Navigate to the “Status” page here and your server should show up. If two do, choose the first
You now have a working Native Jupyter Environemnt (so widgets work etc) off of Colab. (it may take a few minutes before it shows up, its dependent on how long the cell takes to run)
MAKE SURE to end the session when you are done by running
end_session() so the server does not run forever!
To use the master branch from GitHub, run the following:
!pip install git+ !pip install git+
- Note, if you have already installed and began running
fastaicode, you will need to restart your runtime
- It says I can’t get a GPU (no GPU available, why?):
Colab Pro released and so there is a small chance you may not be able to access a GPU. You should try again a little later to see if one opened up. Pro users do not have to worry about this issue