How can I use another language besides English? because Indonesian is detected as Chinese

Rasa Open Source Feedback on Rasa Open Source
1

image
image1366×768 29.8 KB

i’ve tried some alternatives like GitHub - RasaHQ/rasa-nlu-examples: This repository contains examples of custom components for educational purposes. but it’s not working on rasa version 3 already.

so i want to ask. can i use indonlp/indonlu · Datasets at Hugging Face in the config.yml? and if so how?

this is my config.yml

# https://rasa.com/docs/rasa/model-configuration/
recipe: default.v1

# Configuration for Rasa NLU.
# https://rasa.com/docs/rasa/nlu/components/
language: id

pipeline:
# # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
# # If you'd like to customize it, uncomment and adjust the pipeline.
# # See https://rasa.com/docs/rasa/tuning-your-model for more information.
  - name: WhitespaceTokenizer
  - name: RegexEntityExtractor
  - name: RegexFeaturizer
    # # Text will be processed with case sensitive as default
    # case_sensitive: True
    # # use match word boundaries for lookup table
    # use_word_boundaries: True
    # use_lookup_tables: True
    # number_additional_patterns: 10
  - name: LexicalSyntacticFeaturizer
  - name: CountVectorsFeaturizer
  - name: CountVectorsFeaturizer
    analyzer: char_wb
    min_ngram: 1
    max_ngram: 4
  # - name: rasa_nlu_examples.featurizers.dense.BytePairFeaturizer
  #   lang: id
  #   vs: 1000
  #   dim: 25
  - name: DIETClassifier
    epochs: 100
    constrain_similarities: true
  - name: EntitySynonymMapper
  - name: ResponseSelector
    epochs: 100
    constrain_similarities: true
  - name: FallbackClassifier
    threshold: 0.3
    ambiguity_threshold: 0.1
  

# second_pipeline:
# - name: SpacyNLP
#   model: en_core_web_md
# - name: SpacyTokenizer
# - name: SpacyFeaturizer
# - name: RegexFeaturizer
# - name: LexicalSyntacticFeaturizer
# - name: CountVectorsFeaturizer
# - name: CountVectorsFeaturizer
#   analyzer: "char_wb"
#   min_ngram: 1
#   max_ngram: 4
# - name: DIETClassifier
#   epochs: 100
# - name: EntitySynonymMapper
# - name: ResponseSelector
#   epochs: 100


# Configuration for Rasa Core.
# https://rasa.com/docs/rasa/core/policies/
policies:
# # No configuration for policies was provided. The following default policies were used to train your model.
# # If you'd like to customize them, uncomment and adjust the policies.
# # See https://rasa.com/docs/rasa/policies for more information.
  - name: MemoizationPolicy
  - name: RulePolicy
  - name: UnexpecTEDIntentPolicy
    max_history: 8
    epochs: 200
  - name: TEDPolicy
    max_history: 8
    epochs: 200
    constrain_similarities: true

type or paste code here