模型:

microsoft/DialogRPT-updown

英文

示例

请尝试这个 ➤➤➤ Colab Notebook Demo (click me!)

Context Response updown score
I love NLP! Here’s a free textbook (URL) in case anyone needs it. 0.613
I love NLP! Me too! 0.111

上下得分(updown score)预测回应被点赞的可能性有多大。

DialogRPT-updown

对话排序预训练转换器

对话回应有多大可能被点赞?或者得到回复??

这是 DialogRPT 学会预测的东西。它是由 Microsoft Research NLP Group 提出的一组对话回应排序模型,使用了1亿多条人类反馈数据进行训练。可以通过重新排序生成的回应候选集来提高现有的对话生成模型(例如 DialoGPT )。

快速链接:

我们考虑了以下任务,并提供了相应的预训练模型。本页是针对 updown 任务的,其他模型卡片可以在下表中找到。

Task Description Pretrained model
Human feedback given a context and its two human responses, predict...
updown ... which gets more upvotes? this model
width ... which gets more direct replies? 1238321
depth ... which gets longer follow-up thread? 1239321
Human-like (human vs fake) given a context and one human response, distinguish it with...
human_vs_rand ... a random human response 12310321
human_vs_machine ... a machine generated response 12311321

联系方式:

请在 our repo 上创建一个问题。

引用:

@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}
}