a simple message reply suggestion system

Design and build a chatbot using data from the Cornell Movie Dialogues corpus, using Keras

Chatbot implementation using Cornell Movie Dialog Dataset in PyTorch.The bot can converse with the user and can answer the questions asked though it doesn't pass the Turing Test

Tensorflow Chatbot trained with Cornell movie-dialog corpus

ChatBot using Recuurent Neural networks and Cornell Corpus dataset (TensorFlow)

Fine-tuning the GPT-2 model on the Cornell Movie-Dialogues Corpus dataset to create a conversational chatbot.

Realistic Chatbot based on NLP & TensorFlow

I built a chatbot using transformer models trained on datasets like Cornell Movie Dialogs and Reddit chats. It understands and replies like a human by learning context through self-attention. I fine-tuned it to give relevant, consistent, and tone-controlled responses using methods like beam search and sampling.

This is a implementation of Twitter/Cornell-Movie Chatbot Tinu . A sequence2sequence chatbot implementation with TensorFlow 1.10 . I just use 10% data of full dataset. you can use full dataset.Then you need to read full article.

Generative adversarial imitation learning to produce a proxy for the reward function present in dialogue.

Simple Telegram chatbot trained on the Cornell Movie-Dialogs Corpus.

Your Kind Friend Bot: Unreliable Chatbot

Rule based chat-bot using CNN based on multi class text classification which responds to all queries on Deep Learning class. As a fallback option added generative chat-bot trained on cornell movie dialog corpus using sequence to sequence RNN model.