Create trained model vocabulary APIedit
Creates a trained model vocabulary. This is supported only for natural language processing (NLP) models.
Requestedit
PUT _ml/trained_models/<model_id>/vocabulary/
Prerequisitesedit
Requires the manage_ml cluster privilege. This privilege is included in the
machine_learning_admin built-in role.
Descriptionedit
The vocabulary is stored in the index as described in
inference_config.*.vocabulary of the trained model definition.
Path parametersedit
-
<model_id> - (Required, string) The unique identifier of the trained model.
Request bodyedit
-
vocabulary - (array) The model vocabulary. Must not be empty.
-
merges - (Optional, array) The model merges used in byte-pair encoding. The merges must be sub-token pairs, space delimited, and in order of preference. Example: ["f o", "fo o"]. Must be provided for RoBERTa and BART style models.
-
scores -
(Optional, array)
Vocabulary value scores used by sentence-piece tokenization. Must have the same length as
vocabulary. Required for unigram sentence-piece tokenized models like XLMRoberta and T5.
Examplesedit
The following example shows how to create a model vocabulary for a previously stored trained model configuration.
PUT _ml/trained_models/elastic__distilbert-base-uncased-finetuned-conll03-english/vocabulary
{
"vocabulary": [
"[PAD]",
"[unused0]",
...
]
}
The API returns the following results:
{
"acknowledged": true
}