Natural Language Processing course resources
Running on Google Colab
Google has released its own flavour of Jupyter called Colab, which has free GPUs!
Here's how you can use it:
- Open https://colab.research.google.com, click Sign in in the upper right corner, use your Google credentials to sign in.
- Click GITHUB tab, paste https://github.com/hse-aml/natural-language-processing and press Enter
- Choose the notebook you want to open, e.g. week1/week1-MultilabelClassification.ipynb
- Click File -> Save a copy in Drive... to save your progress in Google Drive
- If you need a GPU, click Runtime -> Change runtime type and select GPU in Hardware accelerator box
- Execute the following code in the first cell that downloads dependencies (change for your week number):
! wget https://raw.githubusercontent.com/hse-aml/natural-language-processing/master/setup_google_colab.py -O setup_google_colab.py import setup_google_colab # please, uncomment the week you're working on # setup_google_colab.setup_week1() # setup_google_colab.setup_week2() # setup_google_colab.setup_week3() # setup_google_colab.setup_week4() # setup_google_colab.setup_project() # setup_google_colab.setup_honor()
- If you run many notebooks on Colab, they can continue to eat up memory,
you can kill them with
! pkill -9 python3and check with
! nvidia-smithat GPU memory is freed.
- No support for
ipywidgets, so we cannot use fancy
tqdmprogress bars. For now, we use a simplified version of a progress bar suitable for Colab.
- Blinking animation with
IPython.display.clear_output(). It's usable, but still looking for a workaround.