GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → DataSenseiAryan → TS3000_TheChatBOT

DataSenseiAryan / TS3000_TheChatBOT

Licence: MIT license
Its a social networking chat-bot trained on Reddit dataset . It supports open bounded queries developed on the concept of Neural Machine Translation. Beware of its being sarcastic just like its creator 😝 BDW it uses Pytorch framework and Python3.

Programming Languages

python
139335 projects - #7 most used programming language
Jupyter Notebook
11667 projects

Labels

deep-learningchatbotbeam-searchneural-machine-translationsqlite3-databaseattention-mechanismbidirectional-rnnencoder-decoder-modelpytorch-nlpreddit-datasetpytorch-nmtpytorch-implementationnmt-chatbotsocial-network-chatbot

Projects that are alternatives of or similar to TS3000 TheChatBOT

Pytorch Seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Stars: ✭ 3,418 (+16990%)
Mutual labels:  neural-machine-translation, encoder-decoder-model, pytorch-nlp, pytorch-implementation
minimal-nmt
A minimal nmt example to serve as an seq2seq+attention reference.
Stars: ✭ 36 (+80%)
Mutual labels:  beam-search, neural-machine-translation, attention-mechanism
Sockeye
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Stars: ✭ 990 (+4850%)
Mutual labels:  neural-machine-translation, attention-mechanism
Image-Caption
Using LSTM or Transformer to solve Image Captioning in Pytorch
Stars: ✭ 36 (+80%)
Mutual labels:  beam-search, attention-mechanism
transformer
Neutron: A pytorch based implementation of Transformer and its variants.
Stars: ✭ 60 (+200%)
Mutual labels:  beam-search, neural-machine-translation
Awesome-Pytorch-Tutorials
Awesome Pytorch Tutorials
Stars: ✭ 23 (+15%)
Mutual labels:  pytorch-nlp, pytorch-implementation
DAF3D
Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound
Stars: ✭ 60 (+200%)
Mutual labels:  attention-mechanism, pytorch-implementation
Image Caption Generator
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
Stars: ✭ 126 (+530%)
Mutual labels:  beam-search, attention-mechanism
Tf Seq2seq
Sequence to sequence learning using TensorFlow.
Stars: ✭ 387 (+1835%)
Mutual labels:  beam-search, neural-machine-translation
Seq2seq chatbot
基于seq2seq模型的简单对话系统的tf实现，具有embedding、attention、beam_search等功能，数据集是Cornell Movie Dialogs
Stars: ✭ 308 (+1440%)
Mutual labels:  beam-search, attention-mechanism
DCAN
[AAAI 2020] Code release for "Domain Conditioned Adaptation Network" https://arxiv.org/abs/2005.06717
Stars: ✭ 27 (+35%)
Mutual labels:  attention-mechanism, pytorch-implementation
Poetry Seq2seq
Chinese Poetry Generation
Stars: ✭ 159 (+695%)
Mutual labels:  beam-search, attention-mechanism
rnn-text-classification-tf
Tensorflow implementation of Attention-based Bidirectional RNN text classification.
Stars: ✭ 26 (+30%)
Mutual labels:  attention-mechanism, bidirectional-rnn
Nmt Keras
Neural Machine Translation with Keras
Stars: ✭ 501 (+2405%)
Mutual labels:  neural-machine-translation, attention-mechanism
nlp classification
Implementing nlp papers relevant to classification with PyTorch, gluonnlp
Stars: ✭ 224 (+1020%)
Mutual labels:  pytorch-nlp, pytorch-implementation
Tensorflow end2end speech recognition
End-to-End speech recognition implementation base on TensorFlow (CTC, Attention, and MTL training)
Stars: ✭ 305 (+1425%)
Mutual labels:  beam-search, attention-mechanism
Seq2seq chatbot new
基于seq2seq模型的简单对话系统的tf实现，具有embedding、attention、beam_search等功能，数据集是Cornell Movie Dialogs
Stars: ✭ 144 (+620%)
Mutual labels:  beam-search, attention-mechanism
Text-Classification-LSTMs-PyTorch
The aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.
Stars: ✭ 45 (+125%)
Mutual labels:  pytorch-nlp, pytorch-implementation
triplet-loss-pytorch
Highly efficient PyTorch version of the Semi-hard Triplet loss ⚡️
Stars: ✭ 79 (+295%)
Mutual labels:  pytorch-implementation
uniformer-pytorch
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks, debuted in ICLR 2022
Stars: ✭ 90 (+350%)
Mutual labels:  attention-mechanism
View All Similar Projects ➔

TS3000_TheChatBot

Tony Stark 3000 - The Chat Bot Its a very basic level conversational AI.

Its a social networking chat-bot trained on Reddit dataset . It supports open bounded queries developed on the concept of Neural Machine Translation. Beware of its being sarcastic like its creator 😝 :trollface: BDW it uses Pytorch framework and Python3

Data Preprocessing :

Downoad Reddit Data From Here

Follow These :

  • Put Downloaded data in Data_Preprocessing directory .

  • Unzip the .bz2 file bzip2 -dk filename.bz2

  • Run createDB.py

    python3 createDB.py

    This will create Database from Raw JSON text file which you unzipped earlier.

  • Run createCORPUS.py

    python3 createCORPUS.py

    This will create corpus .For example I created 2011-08small.txt

  • Move this created corpus to Data directory .

Trainining Model :

  • Start training model using this command :

    python3 main.py -tr data/2013-09small.txt -l -lr 0.0001 -it 50000 -b 64 -p 500 -s 1000

  • To resume training from last where yiu left :

    python3 main.py -tr data/2013-09small.txt -l save/model/2013-09small/1-1_512/3000_backup_bidir_model.tar -lr 0.0001 -it 50000 -b 64 -p 500 -s 1000

Testing Model :

  • To test the model in interactive mode :

    python3 main.py -te save/model/2013-09small/1-1_512/3000_backup_bidir_model.tar -c data/2013-09small.txt -i

Acknowledgements :

License :

MIT License

Copyright (c) 2019 Aryan Chaudhary

LICENSE

HitCount

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].