chanana

# iTerm2 saves it's preferences in ~/Library/Preferences/com.googlecode.iterm2.plist in a binary format
# What you need to do is basically copy that somewhere, convert to xml and remove color schemes in the xml files.
$ cd /tmp/
$ cp ~/Library/Preferences/com.googlecode.iterm2.plist .
$ plutil -convert xml1 com.googlecode.iterm2.plist
$ vi com.googlecode.iterm2.plist

# Now remove the color schemes in the <key> and <dict> tags, 
# to make it easier, record a macro in vi to remove the key (e.g: Desert/Solarized) using `dd`,
# and then remove its color dict with `dat` (delete around tag), and repeat the macro until 

chanana

1. Install the GUI extensions module

2. Go to the Nbextensions tab in your jupyter notebook

3. Tick code prettify

4. Paste the following in the json folding to enable black instead of whatever it’s set to:

{
  "python": {
    "library": "import json\ndef black_reformat(cell_text):\n    import black\n    import re\n    cell_text = re.sub('^%', '#%#', cell_text, flags=re.M)\n    try:\n        reformated_text = black.format_str(cell_text, 88)\n    except TypeError:\n        reformated_text = black.format_str(cell_text, mode=black.FileMode(line_length=88))\n    return re.sub('^#%#', '%', reformated_text, flags=re.M)",

chanana

The Illustrated Transformer is fantastic, but I would suggest that those going into it really should read the previous articles in the series to get a foundation to understand it more, plus later articles that go into GPT and BERT, here's the list:

• A Visual and Interactive Guide to the Basics of Neural Networks
• A Visual And Interactive Look at Basic Neural Network Math
• Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention)
• The Illustrated Transformer
• The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning)
• [The Illustrated GPT-2 (Visualizing Transformer Language Models)](https://