Native GLiNER-2 inference

POST

https://api.fastino.ai

gliner-2

curl --request POST \
  --url https://api.fastino.ai/v1/gliner-2 \
  --header 'X-API-Key: <api-key>'

const options = {method: 'POST', headers: {'X-API-Key': '<api-key>'}};

fetch('https://api.fastino.ai/v1/gliner-2', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.fastino.ai/v1/gliner-2",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_HTTPHEADER => [
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.fastino.ai/v1/gliner-2"

	req, _ := http.NewRequest("POST", url, nil)

	req.Header.Add("X-API-Key", "<api-key>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.fastino.ai/v1/gliner-2")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'

response = http.request(request)
puts response.read_body

POST /v1/gliner-2 Run synchronous native GLiNER-2 extraction and classification. The OpenAPI panel on this page is the source of truth for every request field and response field. Use POST /v1/chat/completions when you need a named hosted model, a fine-tuned model, inference persistence, or the OpenAI-compatible envelope. This native endpoint selects the Fastino GLiNER-2 base model for you.

Request schema

The request requires:

text: one string or an array of strings.
schema: the unified GLiNER schema dictionary. The legacy flat label array is deprecated.

It also accepts threshold, include_confidence, include_spans, and format_results. Omit task; it is a deprecated legacy hint and the schema identifies the operation.

Entity extraction example

curl -X POST "https://api.fastino.ai/v1/gliner-2" \
  -H "X-API-Key: $FASTINO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Apple CEO Tim Cook introduced the iPhone in Cupertino.",
    "schema": {
      "entities": [
        {"name": "person", "description": "named individual"},
        {"name": "organization", "description": "business or institution"},
        {"name": "product", "description": "named commercial product"},
        {"name": "location", "description": "city, region, or place"}
      ]
    },
    "threshold": 0.5,
    "include_confidence": true,
    "include_spans": true
  }'

Classification example

curl -X POST "https://api.fastino.ai/v1/gliner-2" \
  -H "X-API-Key: $FASTINO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "The replacement arrived quickly and works perfectly.",
    "schema": {
      "classifications": [
        {
          "task": "sentiment",
          "labels": ["positive", "negative", "neutral"],
          "multi_label": false,
          "top_k": 1
        }
      ]
    }
  }'

Each classic classification requires at least two labels. For every supported entity, classification, structure, relation, record, attribute, and constrained-classification shape, use the complete POST /v1/chat/completions GLiNER schema reference.

Response schema

A successful response contains:

result: the schema-shaped extraction or classification result.
token_usage: the number of input tokens processed.

{
  "result": {
    "entities": [
      {
        "text": "Apple",
        "label": "organization",
        "score": 0.99,
        "start": 0,
        "end": 5
      }
    ]
  },
  "token_usage": 10
}

When text is an array, result is an array in the same input order. Do not send that batch shape through POST /v1/chat/completions; submit those conversations separately.

⌘I

Native GLiNER-2 inference

curl --request POST \
  --url https://api.fastino.ai/v1/gliner-2 \
  --header 'X-API-Key: <api-key>'

const options = {method: 'POST', headers: {'X-API-Key': '<api-key>'}};

fetch('https://api.fastino.ai/v1/gliner-2', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.fastino.ai/v1/gliner-2",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_HTTPHEADER => [
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.fastino.ai/v1/gliner-2"

	req, _ := http.NewRequest("POST", url, nil)

	req.Header.Add("X-API-Key", "<api-key>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.fastino.ai/v1/gliner-2")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'

response = http.request(request)
puts response.read_body

Inference

Training

Request schema

Entity extraction example

Classification example

Response schema

​Request schema

​Entity extraction example

​Classification example

​Response schema

Request schema

Entity extraction example

Classification example

Response schema