Rasa natively supports spaCy models that have a language model attached. But spaCy also offers tokenizers without a model. We support these tokenisers with this component.
In order to use this tool you'll need to ensure that spaCy is installed with Rasa.
pip install rasa[spacy]
You should also be aware that for certain languages extra dependencies are required. More information is given on the spacy documentation.
- lang: the two-letter abbreviation of the language you want to use.
Once downloaded it can be used in a Rasa configuration, like below;
language: en pipeline: - name: rasa_nlu_examples.tokenizers.BlankSpacyTokenizer lang: "en" - name: CountVectorsFeaturizer - name: CountVectorsFeaturizer analyzer: char_wb min_ngram: 1 max_ngram: 4 - name: DIETClassifier epochs: 100