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This is unreleased documentation for Rasa Open Source Documentation Master/Unreleased version.
For the latest released documentation, see the latest version (2.5.x).

Version: Master/Unreleased

rasa.nlu.tokenizers.jieba_tokenizer

JiebaTokenizer Objects

class JiebaTokenizer(Tokenizer)

This tokenizer is a wrapper for Jieba (https://github.com/fxsjy/jieba).

__init__

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

Construct a new intent classifier using the MITIE framework.

load_custom_dictionary

| @staticmethod
| load_custom_dictionary(path: Text) -> None

Load all the custom dictionaries stored in the path.

More information about the dictionaries file format can be found in the documentation of jieba. https://github.com/fxsjy/jieba#load-dictionary

load

| @classmethod
| load(cls, meta: Dict[Text, Any], model_dir: Text, model_metadata: Optional["Metadata"] = None, cached_component: Optional[Component] = None, **kwargs: Any, ,) -> "JiebaTokenizer"

Loads trained component (see parent class for full docstring).

persist

| persist(file_name: Text, model_dir: Text) -> Optional[Dict[Text, Any]]

Persist this model into the passed directory.