I'm following "Hands on Large Language Models" by Alammar. One of the examples is: from transformers import AutoModelForCausalLM, AutoTokenizer colors_list = [ '102;194;165', '252;141;98', '141;160;203', '231;138;195', '166;216;84', '255;217;47' ] def show_tokens(sentence, tokenizer_name): tokenizer = AutoTokenizer.from_pretrained(tokenizer_name) token_ids = tokenizer(sentence).input_ids for idx, t in enumerate(token_ids): print( f'\x1b[0;30;48;2;{colors_list[idx % len(colors_list)]}m' + tokenizer.decode(t) + '\x1b[0m', end=' ' ) text = """ English and CAPITALIZATION 鸟 show_tokens False None elif == >= else: two tabs:" " Three tabs: " " 12.0*50=600 """ show_tokens(text, "bert-base-uncased") Which is supposed to show up as: However, in Visual Studio Code I see it as: Continue reading...