We present a large, tunable neural conversational response generation model,DialoGPT(dialogue generative pre-trained transformer) .
Trained on 147M conversation-like exchanges extracted from Reddit comment chains over a period spanning from 2005 through 2017,
DialoGPT extends the Hugging Face PyTorch transformer to attain a performance close to human both in terms of automatic and human evaluation in single-turn dialogue settings.
We show that conversational systems that leverage DialoGPT generate more relevant, contentful and context-consistent responses than strong baseline systems.
The pre-trained model and training pipeline are publicly released to facilitate research into neural response generation and the development of more intelligent open-domain dialogue systems.