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A lightweight Flask app for ranking message responses based on GPT-2, DialoGPT, and DialogRPT

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GPT2-Ranking

GPT2-Ranking is a lightweight frontend for experiments using the up-down scoring model of Sean Xiang Gao's DialogRPT. It is based on a GPT-2 medium (345M) model, pre-trained on 147M Reddit conversations, with an added linear layer to model a regression that predicts the likelyhood of upvotes for a comment, given a context ( submission text body ). The full model was then trained on 133M context/response pairs of Reddit data from 2011-2012.

Experiments are ongoing.

Local Install

  • Install Dependencies: pip install -r requirements.txt
  • Run server: python main.py
  • Open Web Browser and visit: http://localhost:8080/

Docker Image:

  • Build: docker build -t gpt2-ranking .
  • Run: docker run -p 8080:8080 --rm -d gpt-ranking

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A lightweight Flask app for ranking message responses based on GPT-2, DialoGPT, and DialogRPT

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