Decide selects from labels declared in your schema. It does not produce explanations, conversations, or open-ended answers.
Why use GLiNER 2.5 Decide
- Predictable outputs — the model chooses from labels you define, so downstream code does not parse generated prose.
- Actionable uncertainty — probabilities and confidence support thresholds, fallback handling, and human review.
- Related judgments in one pass — classify intent, urgency, route, and handoff from the same input.
- Flexible schemas — change labels at request time instead of retraining for every taxonomy change.
When to use it
Use GLiNER 2.5 Decide when classification is the primary task:- Intent and routing — send messages or requests to the correct workflow.
- Single-label classification — select exactly one category.
- Multi-label classification — select every applicable tag.
- Operational gates — decide whether an agent finished, a human should take over, or content violates a rule.
- Custom taxonomies — define task-specific labels at request time.
- Several decisions per input — classify multiple independent aspects of the same text in one request.
Start building
Call GLiNER 2.5 Decide
Authenticate and make a first schema-defined classification request.
Classification
Configure tasks and labels, then consume single-label and multi-label results.
Evaluation & Train
Evaluate Decide, select thresholds, and train it for your domain.
Capabilities
Review language, schema behavior, limits, and unsupported patterns.