Create a trained model vocabulary

PUT /_ml/trained_models/{model_id}/vocabulary

Auth

This API is supported only for natural language processing (NLP) models. The vocabulary is stored in the index as described in inference_config.*.vocabulary of the trained model definition.

Required authorization

Cluster privileges manage_ml

Path parameters

model_id string required: The unique identifier of the trained model.

Request body

vocabulary string[] required: The model vocabulary, which must not be empty.
merges string[]: The optional model merges if required by the tokenizer.
scores number[]: The optional vocabulary value scores if required by the tokenizer.

Response

application/json

acknowledged boolean required: For a successful response, this value is always true. On failure, an exception is returned instead.

Examples

Request Console 1 / 8 languages

An example body for a PUT _ml/trained_models/elastic__distilbert-base-uncased-finetuned-conll03-english/vocabulary request.

Console Kibana Dev Tools

PUT _ml/trained_models/elastic__distilbert-base-uncased-finetuned-conll03-english/vocabulary
{
  "vocabulary": [
    "[PAD]",
    "[unused0]",
  ]
}

JavaScript Elasticsearch JavaScript Client

const response = await client.ml.putTrainedModelVocabulary({
  model_id: "elastic__distilbert-base-uncased-finetuned-conll03-english",
  vocabulary: ["[PAD]", "[unused0]"],
});

Python Elasticsearch Python Client

resp = client.ml.put_trained_model_vocabulary(
    model_id="elastic__distilbert-base-uncased-finetuned-conll03-english",
    vocabulary=[
        "[PAD]",
        "[unused0]"
    ],
)

curl Shell

curl -X PUT "$ELASTICSEARCH_URL/_ml/trained_models/elastic__distilbert-base-uncased-finetuned-conll03-english/vocabulary" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "vocabulary": [
      "[PAD]",
      "[unused0]"
    ]
  }'

Java Elasticsearch Java Client

client.ml().putTrainedModelVocabulary(p -> p
    .modelId("elastic__distilbert-base-uncased-finetuned-conll03-english")
    .vocabulary(List.of("[PAD]","[unused0]"))
);

C# Elasticsearch .NET Client

var response = await client.MachineLearning
    .PutTrainedModelVocabularyAsync(modelId: "elastic__distilbert-base-uncased-finetuned-conll03-english", d1 => d1
        .Vocabulary("[PAD]", "[unused0]")
    );

PHP Elasticsearch PHP Client

$resp = $client->ml()->putTrainedModelVocabulary([
    "model_id" => "elastic__distilbert-base-uncased-finetuned-conll03-english",
    "body" => [
        "vocabulary" => array(
            "[PAD]",
            "[unused0]",
        ),
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.ml.put_trained_model_vocabulary(
  model_id: "elastic__distilbert-base-uncased-finetuned-conll03-english",
  body: {
    "vocabulary": [
      "[PAD]",
      "[unused0]"
    ]
  }
)

Response

{
  "acknowledged": false
}

Generated from the API spec

Required authorization

Path parameters

Request body { }

Response

Request body