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
):
dummy
(0), inform (1), question (2), directive (3), commissive (4)
Usage
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)
Runs of diwank dyda-deberta-pair on huggingface.co
29
Total runs
0
24-hour runs
-1
3-day runs
-2
7-day runs
-39
30-day runs
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