Jean-Baptiste/camembert-ner cover image

Jean-Baptiste/camembert-ner

A Named Entity Recognition model fine-tuned from CamemBERT on the Wikiner-FR dataset. Our model achieves high performance on various entities, including Persons, Organizations, Locations, and Miscellaneous entities.

A Named Entity Recognition model fine-tuned from CamemBERT on the Wikiner-FR dataset. Our model achieves high performance on various entities, including Persons, Organizations, Locations, and Miscellaneous entities.

Public
$0.0005 / sec

HTTP/cURL API

You can use cURL or any other http client to run inferences:

curl -X POST \
    -d '{"input": "My name is John Doe and I live in San Francisco."}'  \
    -H "Authorization: bearer $DEEPINFRA_TOKEN"  \
    -H 'Content-Type: application/json'  \
    'https://api.deepinfra.com/v1/inference/Jean-Baptiste/camembert-ner'

which will give you back something similar to:

{
  "results": [
    {
      "entity_group": "B-PER",
      "score": 0.9997528195381165,
      "word": "John",
      "start": 11,
      "end": 15
    },
    {
      "entity_group": "I-PER",
      "score": 0.9995835423469543,
      "word": "Doe",
      "start": 16,
      "end": 19
    },
    {
      "entity_group": "B-LOC",
      "score": 0.9997485280036926,
      "word": "San",
      "start": 34,
      "end": 37
    },
    {
      "entity_group": "I-LOC",
      "score": 0.9994599223136902,
      "word": "Francisco",
      "start": 38,
      "end": 47
    }
  ],
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

Input fields

inputstring

text input


webhookfile

The webhook to call when inference is done, by default you will get the output in the response of your inference request

Input Schema

Output Schema