Show HN: Local pretrained classifiers, GPU not needed

This project packages 13 pretrained text classifiers that run and can be retrained entirely on CPU, lowering infrastructure cost and making lightweight NLP deployment viable for teams without GPUs. For IT organizations, the strategic implication is that common classification tasks—such as spam detection, intent routing, sentiment, and topic labeling—can be embedded into internal workflows quickly, but teams should weigh accuracy limits, uncalibrated probabilities, and fit-for-purpose model selection before production use.