https://www.alexanderjunge.net/categories/til/ Recent content in Til on Alexander Junge's website Hugo -- gohugo.io en-US Tue, 17 Jan 2023 00:00:00 +0000 https://www.alexanderjunge.net/blog/til-fstring-formatting/ Tue, 17 Jan 2023 00:00:00 +0000 https://www.alexanderjunge.net/blog/til-fstring-formatting/ I am a big fan of f-strings in Python. If you are not using them yet, you should! f-strings come with a string formatting syntax that makes it very convenient to create nicely formatted strings. For example, you can introduce padding: >>> v = "test" >>> f"{v:>20}" ' test' Or you can format dates and print weekdays instead: >>> from datetime import datetime >>> print(f"Happy {datetime.now():%A}!") Happy Monday! Or you can round floating point numbers: https://www.alexanderjunge.net/blog/til-yes/ Sun, 27 Nov 2022 00:00:00 +0000 https://www.alexanderjunge.net/blog/til-yes/ Today (well, earlier this week but let’s not be picky here) I learned about the Unix core utility yes. It works like this: $ yes y y y # [ad infinitum until stopped] $ yes no no no no # [ad infinitum until stopped] As you can see, yes either prints y\n until stopped or whatever string you pass it followed by a newline, again continuing until the process is killed. https://www.alexanderjunge.net/blog/til-multi-label-automodelforsequenceclassification/ Sun, 12 Jun 2022 00:00:00 +0000 https://www.alexanderjunge.net/blog/til-multi-label-automodelforsequenceclassification/ 🤗 Hugging Face Transformers AutoModelForSequenceClassification offers a quick way to fine-tune a pre-trained language model for a text classification task. AutoModelForSequenceClassification supports multi-label classification via its problem_type argument: from transformers import AutoModelForSequenceClassification model_ckpt = "distilbert-base-uncased" # etc. num_labels = 10 # etc. model = AutoModelForSequenceClassification.from_pretrained( model_ckpt, num_labels=num_labels, problem_type="multi_label_classification", # this is important ) However, this comes with a few additional requirements on the dataset that I did not find good documentation for online.