fastino/GLiNER2.5-Decide
text-classification model by fastino
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Model card & documentation
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The 340M English classification model in the GLiNER2.5 family. Pass any label set at call time: intent, routing, sentiment, priority, policy, and multi-label tags, in a single forward pass. No prompt template. No generated tokens. Load it with AutoExtractor and ship it locally. A single call can score several heads at once. Single-label tasks return one string. Multi-label tasks return every label above the threshold. Exact-match accuracy on fastino/fast-decisions: 17 domains, 300 held-out examples each, with the same text and candidate labels for every model. The suite is English. Use GLiNER2.5-multi-Decide when the input is multilingual. Domain and label details are on the dataset card. This release is not a general-purpose model. It does not reason, explain, or answer open questions. It is a specialist for operational decisions: customer and banking intent, travel and clinic requests, review sentiment, document type, email and ticket routing, human handoff, agent completion, moderation, severity,…
Read the full model card ↗ · Preview checked 2026-11-04T17:40:58.687Z
Inside the original model card — Document outline
- GLiNER2.5-Decide
- Benchmark
- Install
- Examples
- Customer support intent
- Banking request
- Travel request
- Clinic request
- Review sentiment
- Product aspects
- News topic
- Document type
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
fastino/GLiNER2.5-Decide is a text-classification model repository published by fastino on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-classification
- Library
- transformers
- Recent downloads (30 days)
- 80,932
- Cumulative likes
- 400
- Hugging Face trending score
- 65
- Reported safetensors parameters
- 486,444,053
- Architecture
- Gliner2ForSchemaExtraction
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-23T14:56:12.000Z
- Last modified
- 2026-10-08T20:47:53.000Z
Compatibility and lineage
Reported languages: en
Reported base models: fastino/gliner2-large-v1
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-10T06:39:59.353Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.