Hi Team,
I am trying to use BERT in my DIET intent classifier. The versions are: rasa=2.6.2 rasa_core=0.15.1 rasa_nlu=0.14.5 spacy=2.2.4
But it is not identifying “HFTransformersNLP”.
I also tried using LanguageModelFeaturizer only but then i get KeyError: “LanguageModelFeaturizer”
I am trying to run intent classifier in jupyter notebook config2 = “”" language: “en”
pipeline:
- name: “HFTransformersNLP” model_weights: “bert-base-uncased” model_name: “bert”
- name: “LanguageModelTokenizer” # splits the sentence into tokens
- name: “LanguageModelFeaturizer”
model_name: “bert”
model_weights: “rasa/LaBSE”# uses the pretrained Featurizer
- name: “CountVectorizerFeaturizer” # transform the sentence into a vector representation
- name: “DIETClassifier”
“”" with open("./config2.yml",“w”) as report: report.write(config2) report.close()
training_data = load_data(“nlu.md”)
trainer to educate our pipeline
trainer2 = Trainer(config.load("./config2.yml"))
train the model!
interpreter2 = trainer2.train(training_data)
store it for future use
model_directory = trainer.persist("./models/nlu2", fixed_model_name=“current2”)