notice

This is documentation for Rasa Open Source Documentation v2.1.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (2.5.x).

Version: 2.1.x

rasa.nlu.utils.hugging_face.hf_transformers

HFTransformersNLP Objects

class HFTransformersNLP(Component)

This component is deprecated and will be removed in the future.

Use the LanguageModelFeaturizer instead.

__init__

| __init__(component_config: Optional[Dict[Text, Any]] = None, skip_model_load: bool = False) -> None

Initializes HFTransformsNLP with the models specified.

cache_key

| @classmethod
| cache_key(cls, component_meta: Dict[Text, Any], model_metadata: Metadata) -> Optional[Text]

Cache the component for future use.

Arguments:

  • component_meta - configuration for the component.
  • model_metadata - configuration for the whole pipeline.
  • Returns - key of the cache for future retrievals.

train

| train(training_data: TrainingData, config: Optional[RasaNLUModelConfig] = None, **kwargs: Any, ,) -> None

Compute tokens and dense features for each message in training data.

Arguments:

  • training_data - NLU training data to be tokenized and featurized
  • config - NLU pipeline config consisting of all components.

process

| process(message: Message, **kwargs: Any) -> None

Process an incoming message by computing its tokens and dense features.

Arguments:

  • message - Incoming message object