hjLabs AI Playground
Starting the on-device runtime…
Zero-shot classification lets you invent the categories at query time: type "billing, bug report, feature request, spam" and the model scores your text against each one. It works by reframing the problem as natural language inference with a BART model fine-tuned on MNLI, so no training data and no fine-tuning are involved. It is slower per call than a dedicated classifier but immeasurably faster to set up, and everything runs locally.
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Each label costs one forward pass, so ten labels take ten times as long as one. Up to about a dozen labels stays comfortably interactive on a GPU; beyond that consider training a real classifier.
Yes — switch off the single-label option and each label is scored independently, which is the right mode for tagging.