Dual LSTM Encoder for Dialog Response Generation
Jupyter Notebook
1,571
102 commits
updated Nov 21, 2022
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.
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
Download the train/dev/test data here and extract the acrhive into ./data.
python udc_train.py
python udc_test.py --model_dir=...
python udc_predict.py --model_dir=...
4,941 followers · starred Oct 2016
22 followers · starred Dec 2020
41 followers · starred Aug 2016
94 followers · starred Dec 2016
Dual LSTM Encoder for Dialog Response Generation
Jupyter Notebook
1,571
102 commits
updated Nov 21, 2022
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.
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
Download the train/dev/test data here and extract the acrhive into ./data.
python udc_train.py
python udc_test.py --model_dir=...
python udc_predict.py --model_dir=...
4,941 followers · starred Oct 2016
22 followers · starred Dec 2020
41 followers · starred Aug 2016
94 followers · starred Dec 2016