We present a fine-tuned RoBERTa model for English named entity recognition, achieving high performance on both formal and informal datasets. Our approach uses a simplified version of the CONLL2003 dataset and removes unnecessary prefixes for improved efficiency. The resulting model shows superiority over other models, especially on entities that do not begin with uppercase letters, and can be used for various applications such as email signature detection.

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

```bash
curl -X POST \
    -d '{"input": "My name is John Doe and I live in San Francisco."}'  \
    -H "Authorization: bearer $(deepctl auth token)"  \
    -H 'Content-Type: application/json'  \
    'https://api.deepinfra.com/v1/inference/Jean-Baptiste/roberta-large-ner-english'
```

which will give you back something similar to:

```json
{
  "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
  }
}

```


You can use our command-line tool [deepctl](/docs/getting-started) to run
inferences:

```bash
deepctl infer \
    -m 'Jean-Baptiste/roberta-large-ner-english'  \
    -i 'input=My name is John Doe and I live in San Francisco.'
```

which will give you back something similar to:

```json
{
  "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

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

Jean-Baptiste/roberta-large-ner-english

Web inference not supported yet, please check API tab