readme: ---
  license: mit
  ---
  
  # diwank/dyda-deberta-pair
  
  Deberta-based Daily Dialog style dialog-act annotations classification model. It takes two sentences as inputs (one previous and one current of a dialog). The previous sentence can be an empty string if this is the first utterance of a speaker in a dialog. Outputs one of four labels (exactly as in the [daily-dialog dataset](https://huggingface.co/datasets/daily_dialog) ): *__dummy__ (0), inform (1), question (2), directive (3), commissive (4)*
  
  ## Usage
  
  ```python
  from simpletransformers.classification import (
      ClassificationModel, ClassificationArgs
  )
  
  model = ClassificationModel("deberta", "diwank/dyda-deberta-pair")
  convert_to_label = lambda n: ["__dummy__ (0), inform (1), question (2), directive (3), commissive (4)".split(', ')[i] for i in n]
  
  predictions, raw_outputs = model.predict([["Say what is the meaning of life?", "I dont know"]])
  convert_to_label(predictions)  # inform (1)
  ```