zoukankan      html  css  js  c++  java
  • A neural chatbot using sequence to sequence model with attentional decoder. This is a fully functional chatbot.

    原项目链接:https://github.com/chiphuyen/stanford-tensorflow-tutorials/tree/master/assignments/chatbot

    一个使用序列的神经聊天者使用注意解码器对序列模型进行排序。 这是一个功能齐全的chatbot。

    这是基于Google 翻译 Tensorflow 模型 https://github.com/tensorflow/models/blob/master/tutorials/rnn/translate/

    Chip Huyen 等人的序列到序列模型(2014)

    由Chip Huyen创建为作业3的起始代码,CS 20SI 课程:“用于深度学习研究的 TensorFlow ” cs20si.stanford.edu

    详细的任务讲义和培训时间的信息可以在 http://web.stanford.edu/class/cs20si/assignments/a3.pdf 找到

    A neural chatbot using sequence to sequence model with attentional decoder. This is a fully functional chatbot.

    This is based on Google Translate Tensorflow model https://github.com/tensorflow/models/blob/master/tutorials/rnn/translate/

    Sequence to sequence model by Cho et al.(2014)

    Created by Chip Huyen as the starter code for assignment 3, class CS 20SI: "TensorFlow for Deep Learning Research" cs20si.stanford.edu

    The detailed assignment handout and information on training time can be found at http://web.stanford.edu/class/cs20si/assignments/a3.pdf

    Sample conversation

    HUMAN ++++ hi
    BOT ++++ hi . what ' s your name ?
    HUMAN ++++ i'm chip
    BOT ++++ please .
    HUMAN ++++ please what?
    BOT ++++ i don ' t know what to say .
    HUMAN ++++ where are you from?
    BOT ++++ california .
    HUMAN ++++ do you like california?
    BOT ++++ i ' m okay .
    HUMAN ++++ i like california a lot
    BOT ++++ of what ?
    HUMAN ++++ i live here
    BOT ++++ and what is it ?
    HUMAN ++++ california
    BOT ++++ i don ' t know what to say .
    HUMAN ++++ i'm a student here
    BOT ++++ and get it out of here .
    HUMAN ++++ what do you like to do in your free time?
    BOT ++++ and what about the gun ?
    HUMAN ++++ do you have a gun?
    BOT ++++ yes .
    HUMAN ++++ you're dangerous!
    BOT ++++ i ' m not .
    HUMAN ++++ do you go hunting?
    BOT ++++ i can do .
    HUMAN ++++ what do you hunt?
    BOT ++++ virgin .
    HUMAN ++++ that's very bad
    BOT ++++ and you in love ?
    HUMAN ++++ no i'm not
    BOT ++++ please - -
    HUMAN ++++ okay, i am
    BOT ++++ and you are good .
    HUMAN ++++ yeah i am good too.
    BOT ++++ good good to you .
    HUMAN ++++ are you in love?
    BOT ++++ i ' m ready .
    HUMAN ++++ ready for what?
    BOT ++++ for what ?
    HUMAN ++++ for what?
    BOT ++++ i don ' t know what to say .
    HUMAN ++++ tell me
    BOT ++++ i can do it .
    HUMAN ++++ okay, tell me what you're ready for
    BOT ++++ i ' m doing you .
    HUMAN ++++ no you're not
    BOT ++++ please !
    HUMAN ++++ this is a strange conversation
    BOT ++++ i don ' t know what to say .
    HUMAN ++++ are you a guy?
    BOT ++++ of what ?
    HUMAN ++++ are you a boy?
    BOT ++++ i ' m fine .
    HUMAN ++++ are you a man?
    BOT ++++ i ' m a little .
    HUMAN ++++ what's your name?
    BOT ++++ chris -
    HUMAN ++++ chris who?
    BOT ++++ cornelius .
    HUMAN ++++ so i guess you're a guy.
    BOT ++++ i am .
    HUMAN ++++ okay
    BOT ++++ okay ?
    HUMAN ++++ do you have a girlfriend?
    BOT ++++ i ' m sure .
    HUMAN ++++ what's her name?
    BOT ++++ let ' s talk about something else .
    See output_convo.txt for more sample conversations.

    Usage

    Step 1: create a data folder in your project directory, download the Cornell Movie-Dialogs Corpus from https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html Unzip it

    Step 2: python data.py
    This will do all the pre-processing for the Cornell dataset.

    Step 3: python chatbot.py --mode [train/chat]
    If mode is train, then you train the chatbot. By default, the model will restore the previously trained weights (if there is any) and continue training up on that.

    If you want to start training from scratch, please delete all the checkpoints in the checkpoints folder.

    If the mode is chat, you'll go into the interaction mode with the bot.

    By default, all the conversations you have with the chatbot will be written into the file output_convo.txt in the processed folder. If you run this chatbot, I kindly ask you to send me the output_convo.txt so that I can improve the chatbot. My email is huyenn@stanford.edu

    If you find the tutorial helpful, please head over to Anonymous Chatlog Donation to see how you can help us create the first realistic dialogue dataset.

    Thank you very much!

  • 相关阅读:
    GmSSL 与 OpenSSL 共存的安装方法
    爬虫之ssh证书警告错误
    逆向so文件调试工具IDA基础知识点
    frida- registernatives获取so层动态注册函数
    绑定方法与非绑定方法, 反射
    Elk stack安装部署
    类的继承和组合
    安装部署kafka和zookeeper集群(三节点)
    ELK stack 生产问题
    Elasticsearch删除数据操作,你必须知道的一些坑
  • 原文地址:https://www.cnblogs.com/tensorflownews/p/7434887.html
Copyright © 2011-2022 走看看