模型:

microsoft/DialogRPT-human-vs-machine

英文

演示

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

Context Response human_vs_machine score
I love NLP! I'm not sure if it's a good idea. 0.000
I love NLP! Me too! 0.605

"人机对话评分"是预测响应来自人类而不是机器的可能性的分数。

DialogRPT-人机对话

对话排名预训练Transformer模型

一个对话回复有多大可能会得到点赞?和/或回复?的评分?

这是通过训练于超过1亿人类反馈数据的一系列对话回复排名模型所预测的. 可以通过重新排名生成的回复候选项来改进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。

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

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}
}