This package is used to predict intimacy for questions
question-intimacy is a package used to estimate the intimacy of questions. It is released with
EMNLP 2020 paper
Quantifying Intimacy in Language.
pip is installed, question-intimacy could be installed directly from it:
pip3 install question-intimacy
python>=3.6.0 torch>=1.6.0 transformers >= 3.1.0 numpy math tqdm
Usage and Example
Notes: During your first usage, the package will download a model file automatically, which is about 500MB.
Construct the Predictor Object
>>> from question_intimacy.predict_intimacy import IntimacyEstimator >>> inti = IntimacyEstimator()
Cuda is disabled by default, to allow GPU calculation, please use
>>> from question_intimacy.predict_intimacy import IntimacyEstimator >>> inti = IntimacyEstimator(cuda=True)
predict is the core method of this package,
which takes a single text of a list of texts, and returns a list of raw values in
[-1,1] (higher means more intimate, while lower means less).
# Predict intimacy for one question >>> text = 'What is this movie ?'' >>> inti.predict(text,type='list') -0.2737383 # Predict intimacy for a list of questions (less than a batch) >>> text = ['What is this movie ?','Why do you hate me ?'] >>> inti.predict(text,type='list') [-0.2737383, 0.3481976] # Predict intimacy for a long list of questions >>> text = [a long list of questions] >>> inti.predict(text,type='long_list',tqdm=tqdm) [-0.2737383, 0.3481976, ... ,-0.2737383, 0.3481976]
Jiaxin Pei (firstname.lastname@example.org)
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