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Dual LSTM Encoder for Dialog Response Generation

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Retrieval-Based Conversational Model in Tensorflow (Ubuntu Dialog Corpus)

Overview

The code here implements the Dual LSTM Encoder model from The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems.

Setup

This code uses Python 3 and Tensorflow >= 0.9. Clone the repository and install all required packages:

pip install -U pip
pip install numpy scikit-learn pandas jupyter

Get the Data

Download the train/dev/test data here and extract the acrhive into ./data.

Training

python udc_train.py

Evaluation

python udc_test.py --model_dir=...

Evaluation

python udc_predict.py --model_dir=...

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Dual LSTM Encoder for Dialog Response Generation

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  • Jupyter Notebook 80.7%
  • Python 19.3%