https://github.com/dennybritz/chatbot-retrieval

Dual LSTM Encoder for Dialog Response Generation
https://github.com/dennybritz/chatbot-retrieval

Last synced: 3 months ago
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Dual LSTM Encoder for Dialog Response Generation

• Host: GitHub
• URL: https://github.com/dennybritz/chatbot-retrieval
• Owner: dennybritz
• License: mit
• Created: 2016-04-19T00:52:38.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2022-11-21T20:51:04.000Z (over 1 year ago)
• Last Synced: 2024-01-17T00:53:17.727Z (5 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 19.2 MB
• Stars: 1,580
• Watchers: 108
• Forks: 684
• Open Issues: 61
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-stars-copy - dennybritz/chatbot-retrieval - Dual LSTM Encoder for Dialog Response Generation (Jupyter Notebook)
• my-awesome-stars - dennybritz/chatbot-retrieval - Dual LSTM Encoder for Dialog Response Generation (Jupyter Notebook)

README

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

#### [Please read the blog post for this code](http://www.wildml.com/2016/07/deep-learning-for-chatbots-2-retrieval-based-model-tensorflow)

#### 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](http://arxiv.org/abs/1506.08909).

#### 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](https://drive.google.com/open?id=0B_bZck-ksdkpVEtVc1R6Y01HMWM) 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=...

```