zlm-v1-signal-extract

Text Classification · ZeroGPU

zlm-v1-signal-extract is a specialized ZeroGPU model for turning unstructured text into structured signals that downstream systems can act on.

zlm-v2-iab-classify-edge-enriched

Text Classification · ZeroGPU

zlm-v2-iab-classify-edge-enriched is a multilingual content classification model built for contextual intelligence, advertising, and agent workflows.

zlm-v1-iab-domain-classifier

Text Classification · ZeroGPU

zlm-v1-iab-domain-classifier is a low-latency domain classification model built for advertising, contextual intelligence, and large-scale enrichment workflows.

zlm-v1-iab-classify-edge

Text Classification · ZeroGPU

ZeroGPU's IAB classifier maps any text to the industry-standard IAB Content Taxonomy in a single, fast inference call.

GLiNER2.5 Base v1

Text Classification · Fastino

GLiNER2.5 Base is an English schema-based information extraction model built on DeBERTa-v3-base.

GLiNER2.5 Multi v1

Text Classification · Fastino

GLiNER2.5 Multi is a 287M-parameter multilingual information extraction model built on mDeBERTa-v3-base.

deberta-v3-small

Text Classification · Microsoft

deberta-v3-small is Microsoft’s lightweight text classification model optimized for fast, low-cost zero-shot classification.

GLiNER2.5 Decide v1

Text Classification · Fastino

GLiNER2.5 Decide is a lightweight, zero-shot decision and classification model built for operational AI workflows.