Classify a text into 1-10 of your labels (zero-shot) (Tanod)

Overview

Scores of 1-10 caller-supplied labels for an English text with the nli-deberta-v3-xsmall NLI cross-encoder (Apache-2.0): single-label scores sum to 1 (softmax over the labels), `multi_label` scores each label on its own; sorted best first. Scores are model confidences, not calibrated probabilities. Body: `{"text": "I was charged twice for my subscription this month.", "labels": ["billing", "technical support", "sales"]}`. English only. Runs an open model pinned by hash on Tan

Health