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Context	Response	`width` score
I love NLP!	Can anyone recommend a nice review paper?	0.701
I love NLP!	Me too!	0.029

The width score predicts how likely the response is getting replied.

DialogRPT-width

Dialog Ranking Pretrained Transformers

How likely a dialog response is upvoted 👍 and/or gets replied 💬?

This is what DialogRPT is learned to predict.
It is a set of dialog response ranking models proposed by Microsoft Research NLP Group trained on 100 + millions of human feedback data.
It can be used to improve existing dialog generation model (e.g., DialoGPT ) by re-ranking the generated response candidates. Quick Links:

We considered the following tasks and provided corresponding pretrained models.

Task	Description	Pretrained model
Human feedback	given a context and its two human responses, predict...
`updown`	... which gets more upvotes?	model card
`width`	... which gets more direct replies?	this model
`depth`	... which gets longer follow-up thread?	model card
Human-like (human vs fake)	given a context and one human response, distinguish it with...
`human_vs_rand`	... a random human response	model card
`human_vs_machine`	... a machine generated response	model card

Contact:

Please create an issue on our repo

Citation:

@inproceedings{gao2020dialogrpt,
    title={Dialogue Response RankingTraining with Large-Scale Human Feedback Data},
    author={Xiang Gao and Yizhe Zhang and Michel Galley and Chris Brockett and Bill Dolan},
    year={2020},
    booktitle={EMNLP}
}

microsoft/DialogRPT-width is a pre-trained language model available on the Hugging Face Hub. It's specifically designed for the text-classification task in the transformers library. If you want to learn more about the model's architecture, hyperparameters, limitations, and biases, you can find this information on the model's dedicated Model Card on the Hugging Face Hub . Here's an example API request payload that you can use to obtain predictions from the model:

{
  "inputs": "I like you. I love you"
}

Model Specifications

Last UpdatedJuly 2025

ProviderHuggingFace

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