Seq2seq Chatbot with Attention Mechanism
-
Updated
Aug 25, 2019 - Python
Seq2seq Chatbot with Attention Mechanism
Simple Chatbot
Code and Configuration for Bringing self-attention architectures into real world scenarios
Muturretik muturrerako solasaldi sistema
Implementation of a Seq2Seq deep learning model using PyTorch. Trained model on SQuAD2 data set and interact via a chatbot.
Facebook chatbot that I trained to talk like me using Word2Vec, and LSTMs to build a Sequence to Sequence Model
Automatic Response Generation to Conversational Stimuli
Use a Seq2Seq model to Train a ChatBot
A Deep Learning (RNN-LSTM) Based Chatbot built using the Seq2Seq Model with Keras - Tensorflow.
chatbot using tensor flow seq2seq model
STEVE will be a deep learning general purpose chatbot. Initially it will be completely useless but fun. Later on it could turn useful.
This repository is base on Pytorch Tutorial with some experiments and refined.
Build A task oriented conversational model using seq2seq approaches approaches : without-Attention, with-Attention, with-Transfer Learning
A personified chatbot responding to a query based on the answering pattern of Dr. APJ Abdul Kalam using Information Retrieval, Natural Language Processing, and Deep Learning techniques.
A python based chat-bot based on deep seq2seq model trained to talk and interact like a friend. The system uses a encoder-decoder architecture with each block being a LSTM model. The models were trained on the Movie Dialog dataset and the end product was an interactive python app which could hold a good conversation with a human.
Tensorflow implementation of Seq2Seq-based chatbot (Attention)
Add a description, image, and links to the seq2seq-chatbot topic page so that developers can more easily learn about it.
To associate your repository with the seq2seq-chatbot topic, visit your repo's landing page and select "manage topics."