By model
gliner2-base-v1
Model details for gliner2-base-v1.
POST
gliner2-base-v1 is a versatile extraction-and-classification model for the structured tasks that fill most production pipelines. Point it at any text and, with a single API call, pull named entities by your own labels, populate a typed JSON schema straight from messy input, or classify by sentiment, intent, or topic. No fine-tuning and no prompt engineering, just a label set or schema at inference time. Because it’s purpose-built and CPU-optimized, it runs faster and cheaper than routing this work to a general-purpose frontier model. Reach for gliner-multi-pii-v1 when the job is dedicated PII redaction. When you need clean structure out of raw text, this is the model.References: Model docs • Terms • Privacy
Authorizations
Headers
Optional project identifier. Scopes the request to a specific project when provided.
Body
application/json
Model identifier (fixed for this playground). Use request examples to change use cases.
Allowed value:
"gliner2-base-v1"Example:
"gliner2-base-v1"
Multi-line text or document content to send to the model.
Required string length:
1 - 131072Use-case options for the model. Three use cases are supported:
ner— extract entities for the givenlabels.json— extract structured fields defined by aschema.classification— assign labels from candidate sets defined by aschema.
Response
Success
The response is of type object.

