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How to set pipeline config with other language

post by YYtheFenix on May 14, 2021

After I already test my code with splot task and it’s work well with English.
Now, I change my data to Thai language, train and test. But, the default setting of pipeline is not provide accurate result anymore. I think it cause of tokenization. Therefore, I try to change tokenization method in pipeline as follows:

language: th

pipeline:

• name: “SpacyNLP”
  model: “xx_ent_wiki_sm”
• name: “SpacyTokenizer”

Spacy lib and spacy model “xx_ent_wiki_sm” are both installed.
But it still inaccurate. I have three questions:

1. The following settings is correct or incorrect ?
2. Are there any example for custom tokenization, featurizer and classifier with own custom .py?
3. What is the default settings[tokenization, featurizer, classifier model] of the pipeline? [in case you input nothing]

Thank for your replying

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