Text classifiers in 51 languages that run on your CPU
playground.jeffyclassify.com
playground.jeffyclassify.com
The demo showcases 51 classifiers (the languages from Amazon MASSIVE), all trained on the same set of 60 tasks
When you submit a text, it classifies by first getting the embeddings for the text using a multilingual sentence encoder (paraphrase-multilingual-MiniLM-L12-v2), then running the code through the logistic regression classifier for the corresponding language. The output are a set of %s of how representative the classifier thinks the text is to each class/task, and highlights the highest % one
Training all 60 tasks in 51 languages took 22 minutes of CPU time on a laptop
Accuracy ranges from 60% (Javanese, Filipino) to 86% (English), averaging 76%. Not state-of-the-art, but the classifiers are 10,000× smaller than fine-tuned alternatives and run anywhere without a GPU
Note: the demo is running on a small server, you'll get better performance (ie. lower latency on the requests) if you run it locally (pip install jeffy-classify / GitHub: github.com/nicobrenner/jeffy)