https://github.com/wrannaman/tensorflow-pickup-lines
A pickup line generator using Tensorflow
https://github.com/wrannaman/tensorflow-pickup-lines
Last synced: 29 days ago
JSON representation
A pickup line generator using Tensorflow
- Host: GitHub
- URL: https://github.com/wrannaman/tensorflow-pickup-lines
- Owner: wrannaman
- License: apache-2.0
- Created: 2017-06-25T15:30:46.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-06-25T15:49:49.000Z (over 8 years ago)
- Last Synced: 2025-04-12T06:52:29.004Z (6 months ago)
- Language: Python
- Size: 5.24 MB
- Stars: 17
- Watchers: 3
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Credit
This project was forked from
https://github.com/martin-gorner/tensorflow-rnn-shakespeare
assume all code is attributed to and owned by Martin Gorner.
# Original Code And Presentation
Code for the Recurrent Neural Network in the presentation "Tensorflow and deep learning - without a PhD, Part 2"
The presentation itself is available here:
* [Video](https://t.co/cIePWmdxVE)
* [Slides](https://goo.gl/jrd7AR)
This sample has now been updated for Tensorflow 1.1. Please make sure you redownload the checkpoint files if you use rnn_play.py.
## Usage:
### To Train
#### Step 1 - Train on Twitter Data
```$ python3 rnn_train.py```
This will train the model and save it with checkpoint files.
After training, you can see what the model outputs by using
```$ python3 rnn_play.py```
You will need to replace the files with your checkpoint files.
#### Step 2 - Train on pickup line data
```$ python3 rnn_retrain.py```
You will need to replace the checkpoint file names for this to work.
### To Play
Point to the correct checkpoint files and do
```$ python3 rnn_play.py```
Each training session will generate saved checkpoints as well as save a final model when it has finished. you can monitor the progress using
Tensorboard
```$ tensorboard --logdir="your/log/path"```