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Forked from https://github.com/pbhatia243/Neural_Conversation_Models, which implements seq2seq with beam serach and attention.
Added features:
- Choice of optimizer: SGD/AdaGrad/Adam
- Mecab as tokenizer
- Twitter chatbot
- Python 2.7 or Python 3.3+
- NLTK
- TensorFlow r0.9 (Currently doesn't work on r0.12)
- tweepy (via pip)
- mecab, python-mecab, mecab-ipadic-utf8 (via apt-get)
Data accepted is in the tsv format where first component is the context and second is the reply
To train a model with Ubuntu dataset:
$ python neural_conversation_model.py --train_dir ubuntu/ --en_vocab_size 60000 --size 512 --data_path ubuntu/train.tsv --dev_data ubuntu/valid.tsv --vocab_path ubuntu/60k_vocan.en --attention
To run a twitter bot:
$ python twitter_bot.py